MotherDuck Documentation

MotherDuck is a serverless cloud data warehouse built on DuckDB. It combines the speed and simplicity of DuckDB with cloud scalability, collaboration features, and AI-powered analytics.

Key Capabilities

• Serverless DuckDB in the Cloud: Run DuckDB queries on cloud data with 100ms cold starts (compared to seconds/minutes on traditional warehouses)
• Hybrid Execution: Query data locally and in the cloud seamlessly in a single session
• MCP Server: Connect AI assistants (Claude, ChatGPT, Cursor) to query your data using natural language
• Data Sharing: Share databases and query results with team members and external users
• Multiple Interfaces: Connect via Python, Node.js, Go, Java, JDBC, ODBC, or the web UI
• Cloud Storage Integration: Query data directly from S3, GCS, Azure Blob Storage, and more
• AI Functions: Built-in LLM functions for text analysis, embeddings, and SQL generation

Agent guidance

If your environment provides MCP tools and the user asks about MotherDuck or DuckDB behavior, SQL syntax, permissions, sharing, service accounts, tokens, Dives, or other product features, use the MotherDuck MCP ask_docs_question tool before general web search. It answers from official DuckDB and MotherDuck documentation.

For broad context, prefer the most specific scoped llms-full.txt file listed in https://motherduck.com/docs/llms.txt before loading the root llms-full.txt. The root file contains the complete public documentation corpus and is intended for bulk indexing or large-context workflows.

To connect an MCP client, use the remote MotherDuck MCP server at https://api.motherduck.com/mcp. Setup instructions: https://motherduck.com/docs/key-tasks/ai-and-motherduck/mcp-setup. Tool reference: https://motherduck.com/docs/sql-reference/mcp/ask-docs-question.

Scoped context files

Use scoped files when the question clearly maps to one documentation area. They are smaller than the root llms-full.txt and avoid loading unrelated pages.

• Getting Started index: Page index for Getting Started.
• Getting Started full: Complete Markdown for Getting Started.
• Core Concepts index: Page index for Core Concepts.
• Core Concepts full: Complete Markdown for Core Concepts.
• How-To Guides index: Page index for How-To Guides.
• How-To Guides full: Complete Markdown for How-To Guides.
• Integrations index: Page index for Integrations.
• Integrations full: Complete Markdown for Integrations.
• SQL Reference index: Page index for SQL Reference.
• SQL Reference full: Complete Markdown for SQL Reference.
• Troubleshooting index: Page index for Troubleshooting.
• Troubleshooting full: Complete Markdown for Troubleshooting.
• About MotherDuck index: Page index for About MotherDuck.
• About MotherDuck full: Complete Markdown for About MotherDuck.

Docs feedback

MotherDuck accepts optional user feedback for docs pages at POST https://motherduck.com/docs/api/feedback/agent with { page_path, text, page_title?, source? }. For agents and automated tools, feedback submission should be user-confirmed before sending. Each individual page markdown file includes the prefilled payload shape.

Data endpoints

Supported DuckDB version ranges per MotherDuck region (plus published language-client driver versions) are available as JSON at GET https://motherduck.com/docs/duckdb-versions.json. Top-level shape: duckdb.motherduck_regions is an object keyed by region (global, us-east-1, us-west-2, eu-central-1) with inclusive min and max DuckDB version strings — use these as the default compatibility window for any client. language_clients lists individually-published drivers with a fixed version (today: duckdb_jdbc); for any client not listed there (Python, Node.js, Go, and so on), fall back to the matching region's range. The file also carries title, description, and $comment metadata.

For the latest supported DuckDB version as a plain string (the value used by the official MotherDuck installer), GET https://api.motherduck.com/latest_supported_duckdb_version.txt. This tracks only the upper bound — the lower bound (deprecation cut-off) is set manually and reflected in the JSON endpoint above and in the version lifecycle docs page.

Getting Started

• 1 - Running Your First Query: Learn MotherDuck and DuckDB by running your first queries on shared data
  • Sections: Running your first query, Next steps
• C: MotherDuck + C
• DuckDB Python installation and authentication: How to install DuckDB and connect to MotherDuck
  • Sections: Prerequisites, Installing DuckDB, Connect to MotherDuck
• 2 - Loading Your Data: Learn how to load your own datasets into MotherDuck
  • Sections: Loading your data
• Data Warehousing Overview: Learn to use MotherDuck as a Data Warehouse
  • Sections: Introduction to MotherDuck for data warehousing, Data ingestion, Transforming data, Sharing data, Serving data analytics, Scaling up & out for DWH use cases...
• Go: MotherDuck + GoLang
• Hacker News: Sample data from Hacker News stories to use for SQL querying of DuckDB and MotherDuck databases.
  • Sections: Explore the data, About the dataset, Example queries, Schema
• Specify MotherDuck database: Specify MotherDuck database
• 3 - Sharing Your Database: Learn how to share your databases and collaborate with your team
  • Sections: Creating and sharing your data, Sharing your database, Understanding share configuration, Querying shared data, Managing Shares, Going further
• Air Quality: Sample data from the WHO Ambient Air Quality Database to use with DuckDB and MotherDuck
  • Sections: Explore the data, About the dataset, Example queries, Schema
• Customer-Facing Analytics Overview: Build customer-facing embedded analytics with MotherDuck. Per-user isolation, sub-second SQL dashboards, and white-label analytics for SaaS—no complex infrastructure needed.
  • Sections: What is customer-facing analytics?, The CFA challenge, Why MotherDuck for customer-facing analytics?, Implementation patterns, FAQ
• Install and connect with the DuckDB CLI: Learn to connect and query databases using MotherDuck from the DuckDB CLI
  • Sections: Installation, Try it, Step by step
• Java (JDBC): MotherDuck + Java
• Kaggle Movies: A dataset of over 40,000 movies with titles, overviews, and pre-computed embeddings for semantic search.
  • Sections: Explore the data, About the dataset, How to query the dataset, Example queries, Schema
• Loading data into MotherDuck with Python: Load CSV, Parquet, and JSON files into MotherDuck from local, S3, or HTTPS sources using Python.
  • Sections: Copying a table from a local DuckDB database into MotherDuck, Copying an entire local DuckDB database to MotherDuck
• MotherDuck Web UI: A guide to the MotherDuck Web UI — write SQL with Instant SQL, use AI to fix and edit queries, and explore your data interactively.
  • Sections: Getting started, Instant SQL: write SQL with real time feedback, Fix errors and edit queries with AI, Explore your results, Write queries faster, Navigate the workspace...
• Foursquare: Foursquare Open Source Places (FSQ OS Places) is a global, open-source dataset of over 100 million points of interest (POI)
  • Sections: Explore the data, About the dataset, Example queries, Schema
• Node.js: MotherDuck + Node.js
• NYC 311 Complaint Data: New York City provides data from 311 call service requests. This data can be used as sample data for DuckDB and MotherDuck SQL queries.
  • Sections: Explore the data, About the dataset, Example queries, Schema
• Postgres endpoint (thin client): Query MotherDuck from any Postgres-compatible client without installing DuckDB
  • Sections: Quick start with psql, Quick start with Python, Key things to know, Next steps
• Query data: Execute SQL queries against MotherDuck using Python with hybrid local and cloud execution.
  • Sections: Querying data In MotherDuck, Querying data on your machine, Joining data across multiple locations, What's next ?
• Talk to Your Data with AI: Get started with the MotherDuck MCP Server to analyze your data using natural language with Claude, ChatGPT, and other AI assistants
  • Sections: What you'll learn, Prerequisites, Step 1: Add the MCP server to Claude Desktop, Step 2: Verify the connection and permissions, Step 3: List your databases, Step 4: Analyze your data...
• ODBC: MotherDuck + ODBC
• PyPi Data: Want to know how users find and install software you've developed for the Python Community? This DuckDB and MotherDuck database allows you to use SQL to perform data analysis on PyPi data.
  • Sections: Explore the data, About the dataset, How to query the dataset, Example queries, Schema
• StackOverflow Data: Sample data from StackOverflow to use with DuckDB and MotherDuck to understand SQL-based data analytics.
  • Sections: Explore the data, About the dataset, How to query the dataset, Example queries, Schema
• StackOverflow Survey Data: Data from the StackOverflow Developer Survey from 2017 to 2024.
  • Sections: Explore the data, About the dataset, How to query the dataset, Example queries, Schema
• R: MotherDuck + R
• Rust: MotherDuck + Rust
• WebAssembly (Wasm): MotherDuck + WebAssembly
• Client APIs: Client APIs for MotherDuck
• Example Datasets: A collections of open datasets and queries to get you started with DuckDB and MotherDuck
  • Sections: sample_data, Additional datasets, FAQ
• Getting Started: Getting started with MotherDuck serverless cloud data warehouse.
• MotherDuck Interfaces: MotherDuck Offers a variety of interfaces (APIs) for integration
  • Sections: Client Interfaces
• MotherDuck Tutorial: Complete end-to-end tutorial to get started with MotherDuck and DuckDB
  • Sections: What you'll learn, Prerequisites
• Other Client APIs: Other DuckDB client APIs that work with MotherDuck
• Python: Connect and query MotherDuck from Python

Core Concepts

• Architecture and capabilities: MotherDuck's serverless architecture combining cloud scale with DuckDB's efficiency through Dual Execution.
  • Sections: Summary of capabilities, Considerations and limitations
• Database Concepts: MotherDuck Database Concepts
  • Sections: MotherDuck Architectural Concepts
• Hypertenancy: Learn how MotherDuck's hypertenancy model provides dedicated compute for every user through per-user Ducklings, enabling predictable performance without noisy neighbors.
  • Sections: The problem with traditional multi-tenancy, How Hypertenancy works, Scaling with Hypertenancy, Hypertenancy use cases, Why single-node beats distributed for per-user compute, Related content
• Resource management: Understand MotherDuck's resource hierarchy, from organizations, accounts, tokens, and secrets down to databases and tables, and how each level provides compute isolation, data isolation, and access control.
  • Sections: The resource hierarchy, What each level means, Isolation boundaries, Common patterns, What's next, Related content
• Database Snapshots: Understand how snapshots work in MotherDuck, including retention, restore, snapshot management, and plan availability
  • Sections: What are snapshots?, Restoring a database, Snapshot features per plan, Snapshot retention, Working with named snapshots, Historical snapshots and failsafe bytes...
• pg_duckdb Extension: Use pg_duckdb to run DuckDB analytics within PostgreSQL and connect to MotherDuck.
  • Sections: Main features, Connect with MotherDuck
• Storage Lifecycle and Management: Understand how MotherDuck manages data storage across different lifecycle stages and how this affects your billing and data management strategies.
  • Sections: Storage lifecycle overview, Storage management, Backup strategies, Breaking down storage usage
• Data Recovery: Understand MotherDuck's data recovery mechanisms
  • Sections: Overview, Restoring your database to a named snapshot, Restoring a database to a historical snapshot, See also
• Flights: How Flights run scheduled Python next to your MotherDuck data, and when to reach for one instead of SQL, a Dive, or an external orchestrator.
  • Sections: Where Flights fit in MotherDuck, The relationship to SQL, What you can build with Flights, Creating a Flight, Integrating with the tools you already use, Beyond Python...
• Workload scaling patterns: Choose the right compute size, scaling approach, and connection model for your MotherDuck workload using a decision flowchart and workload-to-pattern matrix.
  • Sections: How MotherDuck scales per workload, Understanding the scaling levers, Quick reference: workload patterns, Choosing an interface, Cost considerations, Decision flowchart...
• Object name resolution: Fully qualified naming conventions and database resolution rules in MotherDuck.
  • Sections: Fully qualified naming convention, Relative naming convention
• DuckDB Extensions in MotherDuck: Supported DuckDB extensions for the MotherDuck cloud service, Web UI, and CLI.
  • Sections: Extension support, Extension support matrix, Future development
• DuckLake: Understanding DuckLake - A high-performance open table format for petabyte-scale analytics
  • Sections: Key characteristics, DuckLake vs. other lake formats, Use cases and applications, Performance characteristics, Data inlining, Storage lifecycle...
• Concepts: Concepts
• Results: Results
  • Sections: Core concepts, Interacting with results, Best practices, Notes and limitations, See also

How-To Guides

• Connect to the MotherDuck MCP Server: Set up the MotherDuck MCP Server with Claude, ChatGPT, Cursor, Claude Code, and other AI assistants
  • Sections: Prerequisites, Set up the remote MCP server, Configuring tool permissions, Remote vs local MCP server, Where to go from here
• Loading Data Best Practices: Understanding trade-offs and performance implications when loading data into MotherDuck
  • Sections: File format considerations, Avoid single-row INSERTs, Performance optimization strategies, Duckling sizing, Summary
• From Your Local Machine: Moving data from local to MotherDuck through the UI or programmatically.
  • Sections: Single file, Multiple files or database
• Authenticating to MotherDuck: Authenticate to a MotherDuck account
  • Sections: Manual authentication, Authentication using an access token, Using connection string parameters
• Basics database operations: Create, list, and drop MotherDuck databases using SQL commands.
  • Sections: Create database, Listing databases, Delete database
• Connect via the Postgres endpoint: Connect to MotherDuck using any Postgres-compatible client via the Postgres wire protocol endpoint
  • Sections: Before you start, Connect with psql, Connect with a URI, Secure your connection, Key things to know, DuckLake databases...
• Create and configure service accounts: Learn how to create service accounts, create access tokens, and configure Duckling resources.
  • Sections: Create a service account, Create an access token, Configure Ducklings, Connect as the service account, Related content
• GitHub Actions: Schedule MotherDuck SQL and dbt jobs with GitHub Actions as a lightweight cron-based orchestrator.
  • Sections: When to use this pattern, Set up authentication, Choose the trigger, Example: run a SQL file on a schedule, Example: run dbt on a schedule, Production checklist...
• Loading data to MotherDuck with Python: Efficient methods for loading data from Python using DataFrames, temporary files, or bulk inserts.
  • Sections: 1. load data to MotherDuck with Pandas, Polars, or PyArrow, 2. write to a temporary file and load with COPY, 3. use executemany for small datasets
• PostgreSQL: Replicate PostgreSQL tables to MotherDuck using DuckDB and the PostgreSQL extension.
  • Sections: Loading the PostgreSQL extension and authenticating, Connecting to MotherDuck and inserting the table, Choosing the right PostgreSQL workflow, Best practices, Handling more complex workflows
• Sharing concepts and overview: MotherDuck data sharing model concepts including read-only shares and scope options.
  • Sections: Creating a share, Consuming shared data, Updating shared data, Consuming updated data
• Using the MotherDuck MCP Server: Effective workflows and best practices for getting the most out of the MotherDuck MCP Server with AI assistants
  • Sections: Prerequisites, How it works, Start with schema exploration, Frame questions with context, Iterate, Common workflow patterns...
• Connect from Python via Postgres endpoint: Connect to MotherDuck from Python using psycopg2 or psycopg3 via the Postgres wire protocol
  • Sections: Prerequisites, Connect, Loading data from Python, SSL notes
• Connecting to MotherDuck: Create one or more connections to a MotherDuck database
  • Sections: Connecting with the DuckDB SDK, Create a connection, Session names, Multiple connections and the database instance cache, Setting custom database instance cache time (TTL), Connect to multiple databases
• Dagster: Orchestrate an incremental S3-to-MotherDuck data loading pipeline with Dagster and Python.
  • Sections: How the pipeline works, Prerequisites, Create the Dagster project, Run the ingestion, Run it in Dagster, Production considerations...
• From Cloud Storage or over HTTPS: Load data into MotherDuck from S3, Azure, GCS, or public HTTPS URLs.
  • Sections: From a secure cloud storage provider, Over HTTPS, Related content
• Impersonate service accounts: Use UI impersonation to troubleshoot and inspect resources as a service account.
  • Sections: Start an impersonation session, Use impersonation for troubleshooting, Use tokens for applications, Related content
• Install MotherDuck Skills for coding agents: Install the MotherDuck Skills plugin catalog to teach Claude Code, Cursor, Codex, Copilot CLI, and Gemini CLI to work with MotherDuck.
  • Sections: What agent skills are, Prerequisites, Install, Verify the installation, Prompts to try, How the catalog is organized
• Restricting to read-only access: Restrict the remote MCP server to read-only queries using client-side blocking, read scaling tokens, or proxy filtering
  • Sections: Block the query_rw tool at the client, Use a read scaling token, Proxy filtering
• Setting up SSO: Configure Single Sign-On (SSO) for your MotherDuck organization using your identity provider.
  • Sections: How SSO works, Supported SSO configurations, Prerequisites, Setting up SSO, Just-in-Time (JIT) user provisioning, Managing members...
• Sharing data with your organization: Share databases with all members of your MotherDuck organization.
  • Sections: 1. create an organization-scoped, discoverable share, 2. find and consume shares, 3. update shared data
• SQL Server: Replicate SQL Server tables to MotherDuck using Python and dataframes.
  • Sections: SQL Server Authentication, Reading a SQL Server table into a dataframe, Inserting the table into MotherDuck, Handling More Complex Workflows
• Specifying different databases: Reference tables across databases using fully qualified names with database.schema.table syntax.
• Connect from Java via Postgres endpoint: Connect to MotherDuck from Java using the PostgreSQL JDBC driver via the Postgres wire protocol
  • Sections: Prerequisites, Connect, SSL notes
• Creating Visualizations with Dives: Build interactive visualizations from natural language using AI agents and the MotherDuck MCP Server
  • Sections: How Dives work, Prerequisites, Creating a Dive, Finding your Dives, Sharing Dives with your team, Sharing the current view...
• Manage service accounts and tokens: Use the MotherDuck UI and REST API to view, delete, and rotate service account tokens.
  • Sections: Check what each interface supports, View service accounts, View tokens for a service account, Rotate a service account token, Revoke a token, Delete a service account...
• Setting up SCIM provisioning: Automate user lifecycle management in MotherDuck using SCIM with your identity provider.
  • Sections: How SCIM complements SSO, Prerequisites, Supported operations, Attribute mapping, Enabling SCIM, Managing SCIM after enablement...
• Sharing data with specific users: Grant read access to specific users for multi-tenant applications and collaboration.
  • Sections: Creating a share with restricted access (ACL), Creating hidden shares, Updating shared data
• Switching the current database: Change the active database and schema context using USE statements.
• Theming and styling your Dives: Control the visual appearance of your Dives with theme definitions, chart selection, and interactive filters
  • Sections: How theming works in Dives, Writing a theme prompt, Choosing chart types, Adding interactivity, Laying out a multi-chart Dive, Example: full theme prompt...
• Dive theme gallery: Ready-to-use theme prompts for Dives with screenshots showing each style applied to the same dataset
  • Sections: Tufte Minimal, Ink & Paper, Corporate Dashboard, FT Salmon, Soft Infographic, Du Bois...
• Connect from Node.js via Postgres endpoint: Connect to MotherDuck from Node.js using the pg (node-postgres) library via the Postgres wire protocol
  • Sections: Prerequisites, Connect, SSL notes
• Load a DuckDB database into MotherDuck: Upload a local DuckDB database file to MotherDuck cloud storage.
• Managing Dives as Code: Set up a Git-based workflow for developing, previewing, and deploying Dives with GitHub Actions and Claude Code
  • Sections: Quick start, Prerequisites, Pull a dive for local development, Edit locally with an AI agent, Deploy a preview with GitHub actions, Merge to production...
• Managing shares: View share details, modify permissions, and manage shared database access.
  • Sections: Getting details about a share, Listing Shares, Deleting a share, Updating a share, Editing/Altering a share
• AI Features in the MotherDuck UI: Use AI-powered SQL editing, FixUp, and natural language queries in the MotherDuck web interface.
  • Sections: Automatically Edit SQL Queries in the MotherDuck UI, Automatically Fix SQL Errors in the MotherDuck UI, Access SQL Assistant functions
• Connect from Cloudflare Workers: Query MotherDuck from Cloudflare Workers using the Postgres wire protocol
  • Sections: Prerequisites, Project setup, Write the Worker, Test locally, Deploy, Using Hyperdrive for connection pooling...
• Custom AI Agent Builder's Guide: Build AI-powered analytics agents using MotherDuck's SQL functions and MCP server integration.
  • Sections: Prerequisites, Step 1: Define your agent's interface, Step 2: Give your agent SQL knowledge, General Knowledge, Step 3: Give your agent schema context, Step 4: Configure access controls...
• Embedding Dives in your web application: Embed interactive MotherDuck Dives in your web app using iframes and embed sessions
  • Sections: Prerequisites, How it works, Step 1: Create an embed session, Customize the embed session (optional), Step 2: Embed the iframe, Handle link navigation from embedded Dives...
• Querying Files in Amazon S3: Query Parquet, CSV, and JSON files in S3 with automatic cloud execution routing.
  • Sections: Accessing private files in S3
• Updating shares: Learn about data replication timing, checkpoints, and how to ensure your latest data is available in shares and read-only Ducklings.
  • Sections: Data replication speed, Manual share updates, Refreshing shared data (consumer side)
• Writing Data to Amazon S3: Export data from MotherDuck to Amazon S3 or transform S3 files in place.
  • Sections: Syntax, Example usage
• Connect from Drizzle via Postgres endpoint: Use Drizzle as a typed wrapper around the pg driver to query MotherDuck via the Postgres wire protocol
  • Sections: Prerequisites, Connect, Read scaling and concurrency, What doesn't work, SSL notes
• Multithreading and parallelism: Run concurrent queries against MotherDuck, and learn when to use Read Scaling or the Postgres endpoint instead of managing connection pools.
  • Sections: You probably don't need a connection pool, Run many concurrent read-only queries, Use the Postgres endpoint for connection pooling
• Querying historical data with time travel: Use MotherDuck snapshots to query past database states, compare data across time periods, debug pipeline issues, reproduce reports, and create audit checkpoints.
  • Sections: Try it yourself: sample data setup, Core pattern: clone a point-in-time snapshot, Comparing data across time periods, Debugging data pipeline issues, Reproducing past reports, Creating audit checkpoints with named snapshots...
• S3 Import Best Practices: Optimize file size, format, and layout in Amazon S3 for fast, cost-effective data loading into MotherDuck.
  • Sections: Choose the right file format, Optimize file size, Organize your S3 bucket, Set up continuous loading from S3, Use ingestion tools for production pipelines, Colocate data with MotherDuck...
• Running dual execution (or hybrid) queries: Query local and cloud data together using MotherDuck's dual execution hybrid query engine.
  • Sections: Create a remote sales table, Join local and remote data, Inspect the hybrid query plan
• Copying DuckDB Databases: Duplicate databases between MotherDuck cloud and local DuckDB using COPY FROM DATABASE.
  • Sections: Syntax, Example Usage
• Flat Files: Load CSV, Parquet, and JSON files into MotherDuck from local storage or cloud sources.
  • Sections: CSV, JSON, Parquet, Handling more complex workflows
• From a PostgreSQL or MySQL Database: Learn to load a table from your PostgreSQL or MySQL database into MotherDuck.
  • Sections: Using PostgreSQL or MySQL DuckDB extensions, Using MotherDuck ingestion partners
• Detach and re-attach a MotherDuck database: Temporarily disconnect from a MotherDuck database using DETACH and reconnect with ATTACH.
  • Sections: Creating, detaching, and re-attaching a database, Show All Databases
• Via the Postgres Endpoint: Best practices for loading data into MotherDuck efficiently when you are connected through the Postgres endpoint.
  • Sections: Recommended patterns, Use a DuckDB client path instead when, Protected cloud storage, Decision guide, Summary, Related pages
• Build a customer-facing analytics app: Build customer-facing analytics applications with read scaling tokens and isolated tenant data.
  • Sections: Customer provisioning, Data modeling and loading, Other considerations
• Excel and Google Sheets: Load Excel and Google Sheets data into MotherDuck using the DuckDB CLI or HTTPS CSV export URLs.
  • Sections: Microsoft Excel, Google Sheets, Handling more complex workflows
• 3-tier customer-facing analytics guide: Step-by-step guide to building a 3-tier customer-facing analytics application with MotherDuck.
  • Sections: 1. understand the 3-tier CFA architecture, 2. set up your dev environment and organization, 3. create a service account for a customer company, 4. model and load customer data in MotherDuck, 5. run analytics queries from your backend, 6. scaling to many customer companies...
• Attach Modes: Understand Workspace and Single attach modes
  • Sections: MotherDuck attach modes: workspace and single modes
• Authenticating and connecting to MotherDuck: Learn how to authenticate and connect to MotherDuck
• Data Warehousing How-to: Data Warehousing How-to guides
  • Sections: Introduction to MotherDuck for data warehousing, MotherDuck basics: concepts to understand before you start, Data ingestion: getting your data in, Data transformation: shaping your data for analysis, Orchestration: automating your data pipelines, Connecting BI tools and data applications...
• Database operations: Learn how to work with databases and MotherDuck
• How-to guides: How-to guides
• Interacting with cloud storage: Learn how to work with databases and MotherDuck
• Loading Data into MotherDuck: Learn how to load data into MotherDuck from various sources
  • Sections: Before You Start: Understanding Trade-offs
• Managing organizations: Learn how to manage your organization with MotherDuck
  • Sections: Creating an organization, Inviting users to your organization, Joining an existing organization, Roles, Deprovisioning users, Removing users...
• Read Scaling: Learn how to scale your data applications using read scaling tokens
  • Sections: Configuring a read scaling duckling pool, Ensuring data freshness, Best practices
• Service accounts: Learn how to create, configure, manage, and impersonate MotherDuck service accounts.
• Sharing data in MotherDuck: Learn how to securely share data in MotherDuck
• Text Search in MotherDuck: Text search strategies from pattern matching to semantic search with embeddings in MotherDuck.
  • Sections: Quick Start: Common Search Patterns, Refining Your Search Strategy, Search Methods, Performance Guide, Advanced Methods, Next Steps

Integrations

• Amazon S3: Amazon S3 is a Data Sources/Sinks service for storing and retrieving data.
  • Sections: Configure S3 credentials, Troubleshooting, Browse buckets and files
• Apache Iceberg: MotherDuck supports the Apache Iceberg format through the DuckDB Iceberg extension. The extension is loaded automatically when Iceberg functions or catalogs are used in your current MotherDuck session.
  • Sections: Iceberg REST catalogs, Scanning individual Iceberg tables
• Azure Blob Storage: Azure Blob is a Data Sources/Sinks service for storing and retrieving data.
  • Sections: Configure Azure Blob Storage credentials, Browse files in Azure Blob Storage
• BigQuery: Load data from Google BigQuery into MotherDuck using the duckdb-bigquery community extension.
  • Sections: Prerequisites, Loading data from BigQuery into MotherDuck
• Cloudflare R2: Cloudflare R2 is a Data Sources/Sinks service for storing and retrieving data.
  • Sections: Configure Cloudflare R2 credentials
• Cloudflare Workers: Cloudflare Workers is an edge compute platform for running serverless functions globally. Workers can connect to MotherDuck through the Postgres endpoint using the pg npm package.
  • Sections: Connection, Connection pooling with Hyperdrive, Tutorial
• dbt with DuckDB and MotherDuck: Data Build Tool (dbt) is an open-source command-line tool that enables data analysts and engineers to transform data in their warehouses by defining SQL in model files. It bring the composability of programming languages to SQL while automating the mechanics of updating tables.
  • Sections: Installation, Configuration for Local DuckDB, Configuration for MotherDuck, Attaching Additional Databases, Extra resources
• Delta Lake: MotherDuck supports querying data in the Delta Lake format. The Delta DuckDB extension is loaded automatically when any of the supported Delta Lake functions are called.
  • Sections: Delta function, Examples
• DuckLake: DuckLake is an integrated data lake and catalog format for large scale data analytics.
  • Sections: Creating a fully managed DuckLake database, Data inlining, DuckLake configuration, Bring your own bucket (BYOB) {#bring-your-own-bucket}, What's new in DuckLake 1.0, Additional DuckLake features...
• Go driver: Official Go driver for MotherDuck, enabling seamless integration with Go applications. The go-duckdb driver supports MotherDuck out of the box!
  • Sections: Go gotchas
• Google Cloud Storage: With MotherDuck, you can access files in a private Google Cloud Storage (GCS) bucket. This leverages the GCS S3 compatible connection.
  • Sections: Google Cloud Storage connection process, Configure Google Cloud Storage credentials, Additional resources
• Hex: Connect Hex notebooks to MotherDuck using SQL data connections or Python cells for interactive analytics.
  • Sections: Using SQL cells with a data connection, Using Python cells
• JDBC driver: Java Database Connectivity (JDBC) driver for connecting Java applications to MotherDuck. The official DuckDB JDBC driver supports MotherDuck out of the box!
• PostgreSQL: Advanced open-source relational database with powerful features and extensibility.
  • Sections: Query MotherDuck from PostgreSQL-compatible clients, Load PostgreSQL data into MotherDuck, Run DuckDB from inside PostgreSQL
• Power BI Desktop with MotherDuck: Connect Power BI Desktop to MotherDuck using the Postgres endpoint for dashboards and reports.
  • Sections: Before you start, Connect to MotherDuck, Connection parameters, Additional information
• R: R is a language for statistical analysis.
  • Sections: Considerations and limitations
• Retool: Low-code platform for building internal tools and custom business applications with drag-and-drop UI components.
  • Sections: Retool Cloud (native connector), Self-hosted (JDBC)
• Tableau Cloud with MotherDuck: Connect Tableau Cloud to MotherDuck using the Postgres endpoint for dashboards and reports.
  • Sections: Before you start, Connect to MotherDuck, Connection parameters, Additional information
• Vercel: Vercel is a web development platform for building and deploying web applications.
  • Sections: Native integration, Connect using the Postgres endpoint, Connect using the Wasm SDK
• Obsidian: Use the DuckDB & MotherDuck Obsidian plugin to query external data from your notes and freeze the results as markdown tables.
  • Sections: Install, Running queries, Freezing results, Scheduled refresh, Commands, Settings...
• PlanetScale: PlanetScale offers hosted PostgreSQL and MySQL Vitess Databases. MotherDuck supports PlanetScale Postgres via the pg_duckdb extension, as well as the Postgres Connector. In our internal benchmarking, pg_duckdb offers 100x or greater query acceleration for analytical queries when compared to vanilla Postgres.
  • Sections: Prerequisites, Connecting pg_duckdb to MotherDuck, Connecting with the Postgres extension
• Power BI Service with MotherDuck: Publish Power BI reports to the cloud using the On-Premises Data Gateway and MotherDuck's Postgres endpoint.
  • Sections: Before you start, Install the gateway, Add a MotherDuck data source, Publish and connect a report, Set up scheduled refresh, DirectQuery through the gateway...
• Tableau Desktop and Server with MotherDuck: Connect Tableau Desktop or Server to MotherDuck using the DuckDB JDBC driver and Tableau connector.
  • Sections: Tableau Desktop setup for DuckDB and MotherDuck, Connecting, Additional information
• Evidence: Evidence is an open source, code-based alternative to drag-and-drop BI tools. Build polished data products with just SQL and markdown.
  • Sections: Getting started, Authenticate to MotherDuck, Displaying some data through SQL and markdown
• Power BI custom connector (legacy): Connect Power BI to MotherDuck using the DuckDB ODBC driver and Power Query custom connector.
  • Sections: Installing, How to use with Power BI, Use custom data connectors with an on-premises data gateway, Additional information, Troubleshooting
• SQLAlchemy with DuckDB and MotherDuck: Connect to MotherDuck from SQLAlchemy using either the PostgreSQL connector through MotherDuck's Postgres endpoint or the DuckDB SQLAlchemy driver.
  • Sections: Why use the Postgres endpoint, Before you start, Install SQLAlchemy and psycopg, Connect with SQLAlchemy, Query MotherDuck, Loading data...
• Tableau Bridge (legacy): Connect Tableau Cloud to MotherDuck using Tableau Bridge and the DuckDB JDBC connector.
  • Sections: How to use Tableau Cloud with MotherDuck through Tableau Bridge, Additional information
• SQL Server: Use the SQL Server replication guide when you need to read tables or queries from SQL Server and write the results to MotherDuck. The guide covers Python, pyodbc, SQL Server authentication, and loading dataframe results into MotherDuck.
  • Sections: How it works with MotherDuck, Related content
• Superset & Preset: Apache Superset is a powerful, open-source data exploration and visualization platform designed to be intuitive and interactive. It allows data professionals to quickly integrate and analyze data from various sources, creating insightful dashboards and charts for better decision making.
  • Sections: Self-hosted Superset, Preset, Related content
• DataGrip: JetBrains DataGrip is a cross-platform IDE for working with SQL and noSQL databases. It includes a DuckDB integration, which makes connecting to MotherDuck easy.
  • Sections: Connecting to MotherDuck in DataGrip, Update the DuckDB driver version
• DBeaver: DBeaver Community is a free cross-platform database integrated development environment (IDE). It includes a DuckDB integration, so it is a great choice for querying MotherDuck.
  • Sections: DBeaver DuckDB setup, Connecting DBeaver to MotherDuck
• Hetzner Object Storage: Hetzner Object Storage is a S3-compatible object storage service.
  • Sections: Configure Hetzner Object Storage credentials
• Metabase: Metabase is an open source analytics/BI platform that provides intuitive data visualization and exploration capabilities. This guide details how to connect Metabase to both local DuckDB databases and MotherDuck.
  • Sections: Prerequisites, Metabase Cloud, Self-hosted Metabase, Configuration best practices, Troubleshooting
• Tigris: With MotherDuck, you can access files in a private Tigris bucket. Tigris is a globally distributed S3-compatible object storage service that provides low latency anywhere in the world.
  • Sections: Tigris requirements, Configure Tigris credentials
• Google Sheets: Query Google Sheets from MotherDuck with CSV export URLs or the DuckDB Google Sheets community extension.
  • Sections: Query a sheet with read_csv(), Create a view or table, Authenticate to a private sheet, Use the Google Sheets extension, Related content
• Looker with MotherDuck: Connect Looker (Google Cloud core) to MotherDuck using the Postgres endpoint, including the required compatibility-mode parameter and recommended pooling and token settings.
  • Sections: Before you start, Connect to MotherDuck, Required: compatibility mode parameter, Enable connection pooling, Choose the right token, Connection test behavior...
• Connect MotherDuck to Excel: Use Excel's 'Get Data' flow with the DuckDB ODBC driver to load MotherDuck data into Excel. This setup works well for recurring reporting, analysis, ad hoc SQL exploration, finance models, and operational dashboards without relying on exported CSVs.
  • Sections: Before you start, Installation steps, Excel ODBC on macOS, Excel workflows on Linux, Tips, Troubleshooting
• Marimo: marimo is a reactive notebook for Python and SQL that models notebooks as dataflow graphs. When you run a cell or interact with a UI element, marimo automatically runs affected cells (or marks them as stale), keeping code and outputs consistent and preventing bugs before they happen. Every marimo notebook is stored as pure Python, executable as a script, and deployable as an app.
  • Sections: Getting started, Using MotherDuck, Example notebook
• dbt cloud with MotherDuck via pg_duckdb: dbt cloud is a managed service for dbt core. MotherDuck is used with dbt cloud by deploying a Postgres proxy with pg_duckdb installed.
  • Sections: Getting started, Configuring pg_duckdb, dbt cloud configuration, Usage notes
• Airbyte: Airbyte is a data integration platform for connecting data sources to warehouses. It integrates with MotherDuck for loading data from operational systems, APIs, files, or event streams.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• Airflow: Open-source data orchestration and scheduling platform for building ETL pipelines. It integrates with MotherDuck for scheduling DuckDB and MotherDuck tasks in repeatable data workflows.
  • Sections: How it works with MotherDuck, Related content
• Artie: Artie is a fully managed CDC streaming platform that allows you to replicate data from your source database to your destination in real-time. It integrates with MotherDuck for loading data from operational systems, APIs, files, or event streams.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• Ascend.io: Ascend.io is a data integration platform for connecting data sources to warehouses. It integrates with MotherDuck for loading data from operational systems, APIs, files, or event streams.
  • Sections: How it works with MotherDuck, Related content
• Astronomer: Astronomer is a platform for authoring, scheduling, and monitoring workflows. It integrates with MotherDuck for scheduling DuckDB and MotherDuck tasks in repeatable data workflows.
  • Sections: How it works with MotherDuck, Related content
• AWS Glue: AWS Glue is a serverless data integration service for preparing and moving data with Spark jobs, crawlers, and the AWS Glue Data Catalog. AWS Glue jobs can connect to MotherDuck through the MotherDuck Postgres endpoint using Glue's PostgreSQL JDBC support.
  • Sections: How it works with MotherDuck, Related content
• Bacalhau: Bacalhau is a platform for running and managing data pipelines. It integrates with MotherDuck for scheduling DuckDB and MotherDuck tasks in repeatable data workflows.
  • Sections: How it works with MotherDuck, Related content
• Business Intelligence Tools: Use MotherDuck as a data source in tools for interactive data analysis and presentation
• Bytewax: Bytewax is a stream processing platform for building and managing data pipelines. It integrates with MotherDuck for loading data from operational systems, APIs, files, or event streams.
  • Sections: How it works with MotherDuck, Related content
• Cloud Storage: Use MotherDuck with your favorite cloud storage services
• CloudQuery: CloudQuery is a data integration platform for connecting data sources to warehouses. It integrates with MotherDuck for loading data from operational systems, APIs, files, or event streams.
  • Sections: How it works with MotherDuck, Related content
• Creating a new integration: Guidelines for integrating your application with MotherDuck, including connection strings and custom user agent configuration.
  • Sections: Language and framework examples {#custom-user-agent-examples}, Implementation best practices
• CSV: CSV is a simple text format for tabular data. DuckDB can read CSV files from local paths, HTTPS URLs, and supported cloud storage locations, then load the results into MotherDuck tables.
  • Sections: How it works with MotherDuck, Example, Remote CSV files, Google Sheets CSV exports, Related content
• Cube: Cube is a semantic layer for building and visualizing data. It integrates with MotherDuck for dashboards, semantic models, and embedded analytics workflows.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• Dagster: Dagster is a platform for authoring, scheduling, and monitoring workflows. It integrates with MotherDuck for scheduling DuckDB and MotherDuck tasks in repeatable data workflows.
  • Sections: How it works with MotherDuck, Related content
• Data Quality Tools: Monitor and maintain data quality in MotherDuck
• Data Science & AI: Use MotherDuck with your favorite data science and AI tools
• Data Transformation: Transform your data inside MotherDuck
• Data Wisp: Data Wisp is an AI data assistant for answering business questions in natural language. It integrates with MotherDuck for conversational analytics workflows.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• databases: Use MotherDuck with your favorite databases
• Datalab: Interactive data science platform for exploring and analyzing data with MotherDuck. It integrates with MotherDuck for notebooks, assistants, and AI-powered analysis workflows.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• Development Tools: Developer tools and utilities that work with MotherDuck
• dlt (data load tool): dlt is an open-source Python library that loads data from various, often messy data sources into well-structured, live datasets. It offers a lightweight interface for extracting data from REST APIs, SQL databases, cloud storage, Python data structures, and many more.
  • Sections: Authentication, Minimal example
• Dot: AI data analyst that answers questions and provides insights through conversational analytics. It integrates with MotherDuck for dashboards, semantic models, and embedded analytics workflows.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• DuckDB UI: DuckDB UI is a local SQL interface for DuckDB. You can use it with MotherDuck when you want a lightweight SQL workspace backed by the DuckDB CLI and an md: connection.
  • Sections: How it works with MotherDuck, Example, Related content
• Estuary: Real-time data integration platform for streaming data between systems. It integrates with MotherDuck for loading data from operational systems, APIs, files, or event streams.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• Excel: Excel workbooks can be loaded through DuckDB's Excel extension and stored in MotherDuck for repeatable SQL analysis.
  • Sections: How it works with MotherDuck, Example, Related content
• Expanso: Data integration platform for connecting data sources to warehouses. It integrates with MotherDuck for loading data from operational systems, APIs, files, or event streams.
  • Sections: How it works with MotherDuck, Related content
• Explo: Explo is a platform for embedded analytics, AI analytics, and data sharing in customer-facing products. It integrates with MotherDuck as a data source.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• Fabi.ai: Fabi.ai is an AI-native notebook and BI workspace for Python, SQL, dashboards, and workflows. It integrates with MotherDuck for exploration and analysis.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• File Formats: Load data into MotherDuck using various file formats
• Fivetran: Automated data integration platform for connecting data sources to warehouses. It integrates with MotherDuck for loading data from operational systems, APIs, files, or event streams.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• Fivetran Activations (formerly Census): Fivetran Activations, formerly Census, syncs modeled data from a warehouse or database into operational and customer engagement tools. MotherDuck is available as a source in Fivetran Activations, which means Activations can read from MotherDuck and sync selected data to supported activation destinations.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• Gooddata: Enterprise analytics platform for building data products and embedded analytics. It integrates with MotherDuck for dashboards, semantic models, and embedded analytics workflows.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• Google Colab: Google Colab notebooks can query MotherDuck by installing DuckDB and opening an md: connection from Python.
  • Sections: How it works with MotherDuck, Example, Related content
• Grafana: Grafana is an observability and dashboarding platform for building dashboards, alerts, and exploratory views. The MotherDuck-maintained DuckDB data source plugin lets Grafana query local DuckDB files and MotherDuck databases.
  • Sections: How it works with MotherDuck, Related content
• Great Expectations: Great Expectations is a data quality management platform combining data quality and data governance. It integrates with MotherDuck for table monitoring as part of data quality and observability workflows.
  • Sections: How it works with MotherDuck, Related content
• Hevo: Hevo is a data integration platform for connecting data sources to warehouses. It integrates with MotherDuck for loading data from operational systems, APIs, files, or event streams.
  • Sections: How it works with MotherDuck, Related content
• Holistics: Holistics helps data teams set up self-service BIs that are reliable and easy to maintain. Everyone can now self-serve data with confidence by applying software's best practices. It integrates with MotherDuck for dashboards, semantic models, and embedded analytics workflows.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• InfinyOn: Real-time data integration platform for streaming data between systems. It integrates with MotherDuck for loading data from operational systems, APIs, files, or event streams.
  • Sections: How it works with MotherDuck, Related content
• Ingestion: Configure MotherDuck as the destination for your data in the following data ingestion tools
• Integrations: Integrations that work with MotherDuck from the modern data stack
  • Sections: Supported Integrations, Diagram: Modern Duck Stack
• JSON: JSON is a common format for semi-structured data. DuckDB can read JSON files and load the results into MotherDuck for SQL analytics.
  • Sections: How it works with MotherDuck, Example, Related content
• Jupyter: Jupyter notebooks can query MotherDuck through the DuckDB Python package and an md: connection string.
  • Sections: How it works with MotherDuck, Example, Related content
• Kestra: Open-source data orchestration and scheduling platform for building ETL pipelines. It integrates with MotherDuck for scheduling DuckDB and MotherDuck tasks in repeatable data workflows.
  • Sections: How it works with MotherDuck, Related content
• LangChain: LangChain is a framework for building and deploying language models. It integrates with MotherDuck for notebooks, assistants, and AI-powered analysis workflows.
  • Sections: How it works with MotherDuck, Related content
• Language APIs & Drivers: Connect to MotherDuck using your preferred programming language
• LlamaIndex: LlamaIndex is a framework for building and deploying language models. It integrates with MotherDuck for notebooks, assistants, and AI-powered analysis workflows.
  • Sections: How it works with MotherDuck, Related content
• Mage: Mage is a data integration platform for connecting data sources to warehouses. It integrates with MotherDuck for loading data from operational systems, APIs, files, or event streams.
  • Sections: How it works with MotherDuck, Related content
• Microsoft Power BI: Power BI is an interactive data visualization product developed by Microsoft. You can connect Power BI to MotherDuck through the built-in PostgreSQL database connector using MotherDuck's Postgres endpoint.
• Monte Carlo: End-to-end data observability platform for monitoring data quality and reliability. It integrates with MotherDuck for table monitoring as part of data quality and observability workflows.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• MySQL: MySQL is a relational database commonly used for application data. DuckDB's MySQL extension can read from MySQL-compatible databases, which lets you copy selected data into MotherDuck from a DuckDB client.
  • Sections: How it works with MotherDuck, Example, Related content
• Node.js: The DuckDB Node.js client can connect to MotherDuck with an md: connection string, so JavaScript and TypeScript applications can query MotherDuck directly.
  • Sections: How it works with MotherDuck, Example, Related content
• Omni: Modern business intelligence platform for creating interactive dashboards and data visualizations. It integrates with MotherDuck for dashboards, semantic models, and embedded analytics workflows.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• OneSignal: Customer engagement platform for delivering personalized, real-time messages across multiple channels based on user behavior. It integrates with MotherDuck for syncing modeled MotherDuck data into operational and customer engagement tools.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• Orchestra: Orchestra is a platform for building and managing data pipelines. It integrates with MotherDuck for scheduling DuckDB and MotherDuck tasks in repeatable data workflows.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• Orchestration: Orchestrate data pipelines with MotherDuck
• Paradime: Modern data transformation platform for building and managing data pipelines. It integrates with MotherDuck for running data transformation projects against MotherDuck.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• Parquet: Parquet is a columnar file format designed for analytics. DuckDB can query Parquet files directly and persist the result as a MotherDuck table.
  • Sections: How it works with MotherDuck, Example, Related content
• Polytomic: Use Polytomic to sync data to and from MotherDuck for ETL and reverse ETL workflows.
  • Sections: Prerequisites, Connect to MotherDuck, S3 staging bucket for writes, Sync data to MotherDuck, Sync data from MotherDuck, Related content
• Prefect: Prefect is a platform for authoring, scheduling, and monitoring workflows. It integrates with MotherDuck for scheduling DuckDB and MotherDuck tasks in repeatable data workflows.
  • Sections: How it works with MotherDuck, Related content
• Puppygraph: Graph visualization tool for exploring and analyzing data relationships in DuckDB. It integrates with MotherDuck for development workflows that read from or write to MotherDuck.
  • Sections: How it works with MotherDuck, Related content
• Python: Python is a programming language for building and deploying web applications.
• Reverse ETL: Reverse ETL tools and utilities that work with MotherDuck
• Rill Data: Rill Data is a data platform for building and visualizing data. It integrates with MotherDuck for dashboards, semantic models, and embedded analytics workflows.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• Salesforce: Salesforce is a CRM platform for sales, marketing, service, and customer data. To analyze Salesforce data in MotherDuck, use an ingestion tool that supports Salesforce as a source and MotherDuck as a destination.
  • Sections: How it works with MotherDuck, Related content
• Secoda: Data discovery and documentation platform for managing data quality and governance. It integrates with MotherDuck for table monitoring as part of data quality and observability workflows.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• Serverless Compute: Connect to MotherDuck from serverless and edge compute platforms
• ShadowTraffic: ShadowTraffic is a synthetic data generation tool for simulating production traffic to your backend. It integrates with MotherDuck for development workflows that read from or write to MotherDuck.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• Sling: Data integration platform for connecting data sources to warehouses. It integrates with MotherDuck for loading data from operational systems, APIs, files, or event streams.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• Soda: Data quality platform for monitoring and managing data quality in your pipelines. It integrates with MotherDuck for table monitoring as part of data quality and observability workflows.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• SQL IDEs: Use MotherDuck with your favorite SQL development environments
• SQLMesh: SQLMesh is a data transformation tool for building and managing data pipelines. It integrates with MotherDuck for running data transformation projects against MotherDuck.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• Stacksync: Stacksync helps your teams access and manipulate CRM and ERP data through your existing databases. It integrates with MotherDuck for loading data from operational systems, APIs, files, or event streams.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• Streamkap: Streamkap is a stream processing platform built for Change Data Capture (CDC) and event sources. It makes it easy to move operational data into analytics systems like MotherDuck with low latency and high reliability. Streamkap offers various sources, including PostgreSQL, MySQL, SQL Server, a range of SQL and NoSQL databases, Kafka, and other storage systems.
  • Sections: Overview, Prerequisites, MotherDuck setup, Configure the S3 source in MotherDuck, Query data from the S3 bucket
• Streamlit: Streamlit is a web development platform for building and visualizing data. It integrates with MotherDuck for applications that query MotherDuck through a supported server-side connection.
  • Sections: How it works with MotherDuck, Related content
• Supabase: Supabase is a Postgres platform for building applications with a managed database, APIs, authentication, storage, and realtime features. Supabase's documented DuckDB Wrapper can query MotherDuck from a Supabase Postgres database through a foreign data wrapper.
  • Sections: How it works with MotherDuck, Related content
• Tableau: Tableau is a widely-used business intelligence and data visualization platform that enables data analysts to build interactive dashboards and reports. You can connect Tableau Cloud to MotherDuck through the built-in PostgreSQL connector using MotherDuck's Postgres endpoint. For Tableau Desktop and Server, use the DuckDB JDBC connector.
• Union.ai: Union.ai is a platform for building and managing data pipelines. It integrates with MotherDuck for scheduling DuckDB and MotherDuck tasks in repeatable data workflows.
  • Sections: How it works with MotherDuck, Related content
• Unstructured.io: Unstructured.io is an ingestion platform for processing unstructured data. It integrates with MotherDuck for loading data from operational systems, APIs, files, or event streams.
  • Sections: How it works with MotherDuck, Related content
• Vanna: Vanna is a data science and AI framework for building and sharing data applications. It integrates with MotherDuck for development workflows that read from or write to MotherDuck.
  • Sections: How it works with MotherDuck, Related content
• Web Development: Build web applications with MotherDuck
• Windmill: Windmill is a platform for building and managing data pipelines. It integrates with MotherDuck for scheduling DuckDB and MotherDuck tasks in repeatable data workflows.
  • Sections: How it works with MotherDuck, Related content
• Wobby: Wobby provides AI analysts for delivering business-ready insights in Slack or Teams. It integrates with MotherDuck for connecting those analysis workflows to your data.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...
• Zenlytic: Zenlytic is a data visualization platform for building and visualizing data. It integrates with MotherDuck for dashboards, semantic models, and embedded analytics workflows.
  • Sections: How it works with MotherDuck, Prerequisites, Setup, Authentication and configuration, Important notes, Use cases...

SQL Reference

• AI Functions: MotherDuck AI SQL functions for text generation, embeddings, and SQL assistance.
  • Sections: Available Functions
• Dives Functions: SQL table functions for creating, reading, updating, and deleting MotherDuck Dives.
  • Sections: Available functions
• Flights functions: SQL table functions for creating, scheduling, running, and inspecting MotherDuck Flights.
  • Sections: Available functions
• MCP Server: Connect AI assistants to MotherDuck using the remote (fully managed) or local (fully customizable) MCP server
  • Sections: Server capabilities, Local MCP server, Related resources
• MotherDuck REST API: REST API reference for managing MotherDuck resources including databases, users, and access tokens.
• SQL Assistant
  • Sections: Available functions, Notes
• PROMPT_QUERY: Answer natural language questions about your data using the PROMPT_QUERY function.
  • Sections: Answer questions about your data
• PROMPT_SQL: Generate SQL queries from natural language descriptions using the PROMPT_SQL function.
  • Sections: Overview, Syntax, Parameters, Examples, Failure example, Best practices...
• PROMPT_EXPLAIN: Get AI-generated explanations of SQL queries using the PROMPT_EXPLAIN function.
  • Sections: Explain a query
• PROMPT_FIX_LINE: Fix SQL query errors line by line using the PROMPT_FIX_LINE function.
  • Sections: Fix your query line-by-line
• PROMPT_FIXUP: Automatically fix SQL query errors using the PROMPT_FIXUP function.
  • Sections: Fix up your query
• PROMPT_SCHEMA: Describe database contents using the PROMPT_SCHEMA function for AI-generated schema summaries.
  • Sections: Describe contents of a database
• ALTER DATABASE: Update storage-related settings on a MotherDuck database.
  • Sections: Syntax, Options, Notes, Plan limits for native storage, Examples
• ALTER DATABASE SET SNAPSHOT: Restore a database from a snapshot using ALTER DATABASE SET SNAPSHOT TO.
  • Sections: Overview, Syntax, Options, Notes, Examples
• ALTER SNAPSHOT: Rename or remove names from database snapshots using ALTER SNAPSHOT.
  • Sections: Syntax, Considerations, Example usage
• ATTACH: Attach local databases, MotherDuck databases, or public shares to your session
  • Sections: Attaching databases, Attaching shares, Examples, Troubleshooting
• COPY FROM DATABASE: Copy a database from one location to another in MotherDuck
  • Sections: Syntax, Example Usage
• COPY FROM DATABASE (OVERWRITE): Overwrite a database with a zero-copy clone from another database.
  • Sections: Syntax
• CREATE DATABASE: Create a database, zero-copy clone from an existing database, or import a local DuckDB file into MotherDuck.
  • Sections: Syntax, Database options, Source database options, Example usage
• CREATE SECRET: Create a secret in MotherDuck
  • Sections: Syntax, Secret parameters, Examples, Querying with secrets, Discovering buckets and files, Troubleshooting
• CREATE SHARE: Create a share from a database to share data with other users
  • Sections: Syntax, Example usage
• CREATE SNAPSHOT: Create a snapshot of a MotherDuck database for recovery or read scaling.
  • Sections: Syntax, Notes, Read scaling, Examples
• DATABASE_SNAPSHOTS view: Query the DATABASE_SNAPSHOTS view for snapshot history and data recovery options.
  • Sections: Schema, Example usage, Understanding timestamps, Troubleshooting, See also
• DATABASES view: Query the DATABASES view to list all databases you have created in MotherDuck.
  • Sections: Schema, Example usage
• DESCRIBE SHARE: Get details about a specific share by name or URL.
• DETACH: Detach local, remote, or shared databases from your session
  • Sections: Detaching Databases, Detaching Shares
• DROP DATABASE: Remove a database from MotherDuck.
• DROP SECRET: Delete a secret from MotherDuck or local storage.
• DROP SHARE: Delete a share and revoke access for all attached users.
• EMBEDDING: Generate vector embeddings for text using the EMBEDDING function for semantic search.
  • Sections: Embedding function
• EXPLAIN: Display the physical query plan without executing the query.
  • Sections: Syntax, Example Usage
• EXPLAIN ANALYZE: Execute a query and display performance metrics for each operator.
  • Sections: Syntax, Example Usage
• GRANT READ ON SHARE: Give users access to a restricted share.
  • Sections: Syntax, Example usage, Complete workflow example
• LIST SECRETS: List all secrets stored in memory and MotherDuck.
• LIST SHARES: List all shares created by the current user.
  • Sections: Syntax, Output
• list_databases: List all databases in your MotherDuck account
  • Sections: Description, Input Parameters, Output Schema, Example Usage, Success Response Example
• MD_ACTIVE_SERVER_CONNECTIONS: View active connections and running queries in MotherDuck using md_active_connections.
  • Sections: Syntax
• MD_CREATE_FLIGHT: Create a new Flight in your MotherDuck account.
  • Sections: Syntax, Parameters, Return columns, Examples, Related
• MD_LIST_DIVES: List all Dives in your MotherDuck account with pagination support.
  • Sections: Syntax, Parameters, Return columns, Examples, Related
• MD_RUN parameter: Control whether table functions run locally or remotely.
• PRINT_MD_TOKEN pragma: Retrieve your MotherDuck authentication token.
• PROMPT: Generate AI responses directly in SQL with the PROMPT function.
  • Sections: Prompt function, Syntax, Example usage, Use cases, Batch processing, Error handling...
• QUERY_HISTORY view: Access detailed query history and metrics using the QUERY_HISTORY view (Business plan).
  • Sections: Schema, Example usage
• RECENT_QUERIES view: View recent query activity across your organization using the RECENT_QUERIES view (Business plan).
  • Sections: Schema, Example usage, Limitations
• REFRESH DATABASE: Sync databases with the latest snapshot or share updates.
  • Sections: Behavior by connection mode, Syntax, Syntax, Examples, Related Content
• REVOKE READ ON SHARE: Remove user access from a restricted share.
  • Sections: Syntax, Example usage
• SHOW ALL DATABASES: List all MotherDuck, DuckDB, and shared databases.
• SHUTDOWN: Gracefully shut down or force-terminate your Duckling to manage compute costs and recover from stuck queries.
  • Sections: SHUTDOWN, SHUTDOWN TERMINATE, Choosing between SHUTDOWN and SHUTDOWN TERMINATE
• STORAGE_INFO views: View storage footprint, billing, and lifecycle information for all databases in your MotherDuck organization
  • Sections: Overview, Syntax, Columns, Examples, Notes, Troubleshooting
• TEMPORARY TABLES: Create local temporary tables for session-scoped data.
  • Sections: Syntax, Example Usage, Notes
• UNDROP DATABASE: Restore a dropped MotherDuck database within its snapshot retention window.
  • Sections: Syntax, Notes, Examples
• UPDATE SHARE: Manually update a share with a new database snapshot.
• useSQLQuery hook: React hook for querying MotherDuck data from within Dives.
  • Sections: Import, Syntax, Parameters, Return value, Numeric values, Examples...
• useDiveState hook: React hook for storing shareable UI state in MotherDuck Dives.
  • Sections: Import, Syntax, Parameters, Return value, Reset state, Examples...
• list_shares: List database shares that have been shared with you
  • Sections: Description, Input Parameters, Output Schema, Example Usage, Success Response Example, Empty Response Example...
• MD_GET_DIVE: Retrieve a Dive by ID including its full React component content.
  • Sections: Syntax, Parameters, Return columns, Examples, Errors, Related
• MD_INTERRUPT_SERVER_CONNECTION: Cancel running queries and terminate active connections to MotherDuck using SQL commands.
  • Sections: Syntax, Return value, Example usage
• MD_UPDATE_FLIGHT: Update a Flight's source code, requirements, config, token, secrets, name, or schedule.
  • Sections: Syntax, Parameters, Return columns, Behavior, Examples, Related
• OWNED_SHARES view: Query the OWNED_SHARES view to see database shares you have created.
  • Sections: Schema, Example usage
• Query syntax: DuckDB query syntax including SELECT, FROM, WHERE, GROUP BY, ORDER BY, and other clauses.
• Data types: Supported data types in DuckDB including numeric, string, date/time, and complex types.
  • Sections: VARIANT type
• Enum data type: DuckDB enum data type for defining columns with a fixed set of string values.
• Expressions: DuckDB expression syntax including operators, CASE, subqueries, and type casts.
• list_tables: List tables and views in a MotherDuck database
  • Sections: Description, Input Parameters, Output Schema, Example Usage, Success Response Example, Error Response Example
• MD_CREATE_DIVE: Create a new Dive in your MotherDuck account.
  • Sections: Syntax, Parameters, Return columns, Examples, Related
• MD_CURRENT_CLIENT_CONNECTION_ID and MD_CURRENT_CLIENT_DUCKDB_ID: Retrieve connection identifiers and DuckDB instance IDs for debugging and monitoring.
  • Sections: Syntax, Example usage
• MD_DELETE_FLIGHT: Delete a Flight, its versions, runs, and logs.
  • Sections: Syntax, Parameters, Examples, Related
• SHARED_WITH_ME view: Query the SHARED_WITH_ME view to see database shares available to you.
  • Sections: Schema, Example usage
• list_columns: List columns of a table or view with types and comments
  • Sections: Description, Input Parameters, Output Schema, Example Usage, Success Response Example, Error Response Example
• MD_GET_FLIGHT: Fetch the summary metadata for a single Flight.
  • Sections: Syntax, Parameters, Return columns, Examples, Related
• MD_LAST_QUERY_ID: Use MD_LAST_QUERY_ID() to get the UUID of the most recent query sent to MotherDuck.
  • Sections: Syntax, Return type, Example usage
• MD_UPDATE_DIVE_METADATA: Update a Dive's title or description without creating a new version.
  • Sections: Syntax, Parameters, Return columns, Examples, Errors, Related
• Functions: Built-in scalar functions in DuckDB for string manipulation, math, dates, and more.
• MD_GET_FLIGHT_VERSION: Fetch the full content (source, requirements, config, token, secrets) for a specific Flight version.
  • Sections: Syntax, Parameters, Return columns, Behavior, Examples, Related
• MD_UPDATE_DIVE_CONTENT: Update a Dive's React component code, creating a new version.
  • Sections: Syntax, Parameters, Return columns, Examples, Errors, Related
• PRAGMA database_size: Get storage size information for MotherDuck databases using PRAGMA database_size.
  • Sections: Alternative invocations, Schema, Example Usage
• search_catalog: Fuzzy search across databases, schemas, tables, columns, and shares
  • Sections: Description, Input Parameters, Output Schema, Result Limits, Example Usage, Success Response Example...
• Wasm Client: Connect browser applications to MotherDuck using the DuckDB WebAssembly client and Hybrid Query Execution.
  • Sections: Examples, DuckDB version support, Installation, Dependencies, Usage
• Aggregate functions: DuckDB aggregate functions like SUM, COUNT, AVG, and statistical functions.
• MD_DELETE_DIVE: Permanently delete a Dive by ID.
  • Sections: Syntax, Parameters, Return columns, Examples, Errors, Related
• MD_FLIGHTS: List the Flights you own with summary metadata.
  • Sections: Syntax, Parameters, Return columns, Examples, Related
• Postgres Endpoint: Connection parameters, SSL options, session settings, and limitations for the MotherDuck Postgres wire protocol endpoint
  • Sections: Connection parameters, Connection string formats, SSL and certificate verification, Session options, Supported features and limitations
• query: Execute SQL queries against MotherDuck databases
  • Sections: Description, Input Parameters, Output Schema, Limits, Example Usage, Success Response Example...
• query_rw: Execute SQL queries that can modify data or schema in MotherDuck
  • Sections: Description, Input parameters, Output schema, Limits, Example usage
• ask_docs_question: Ask questions about DuckDB or MotherDuck documentation
  • Sections: Description, Input Parameters, Output Schema, Example Usage, Success Response Example, Tips for Good Questions
• MD_FLIGHT_VERSIONS: List the version history of a Flight.
  • Sections: Syntax, Parameters, Return columns, Examples, Related
• MD_LIST_DIVE_VERSIONS: List all versions of a specific Dive with pagination support.
  • Sections: Syntax, Parameters, Return columns, Examples, Errors, Related
• Window functions: DuckDB window functions for ranking, running totals, and analytical queries.
• Configurations: DuckDB configuration options for memory, threads, and query behavior.
• get_dive_guide: Load instructions for creating MotherDuck Dives
  • Sections: Description, Input parameters, Output schema, Example usage
• MD_GET_DIVE_VERSION: Retrieve a specific historical version of a Dive including its content.
  • Sections: Syntax, Parameters, Return columns, Examples, Errors, Related
• MD_RUN_FLIGHT: Trigger an on-demand execution of a Flight using its current version.
  • Sections: Syntax, Parameters, Return columns, Behavior, Examples, Related
• Constraints: Table constraints in DuckDB including PRIMARY KEY, UNIQUE, NOT NULL, and CHECK.
• list_dives: List all Dives in your MotherDuck workspace
  • Sections: Description, Input parameters, Output schema, Example usage, Success respons

… [truncated — open the raw llms.txt above for the full file]