DuckDB is an in-process
SQL OLAP database management system

Why DuckDB?

Simple and portable

  • In-process, serverless
  • C++11, no dependencies, single-file build
  • APIs for Python, R, Java, Julia, Swift, …
  • Runs on Windows, Linux, macOS, OpenBSD, …


  • Transactions, persistence
  • Extensive SQL support
  • Direct Parquet, CSV, and JSON querying
  • Joins, aggregates, window functions


  • Optimized for analytics
  • Vectorized and parallel engine
  • Larger than memory processing
  • Parallel Parquet, CSV, and NDJSON loaders

Free and extensible

  • Free & open-source
  • Permissive MIT License
  • Flexible extension mechanism

All the benefits of a database, none of the hassle.


Choose your environment to use for DuckDB

  • Command Line
  • Python
  • R
  • Java
  • Node.js
  • ODBC

Latest release: DuckDB 0.9.0 System detected: Other Installations

When to use DuckDB

  • Processing and storing tabular datasets, e.g., from CSV or Parquet files
  • Interactive data analysis, e.g., join & aggregate multiple large tables
  • Concurrent large changes, to multiple large tables, e.g., appending rows, adding/removing/updating columns
  • Large result set transfer to client

When to not use DuckDB

  • High-volume transactional use cases (e.g., tracking orders in a webshop)
  • Large client/server installations for centralized enterprise data warehousing
  • Writing to a single database from multiple concurrent processes
  • Multiple concurrent processes reading from a single writable database



Announcing DuckDB 0.9.0

The DuckDB team is happy to announce the latest DuckDB release (0.9.0). This release is named Undulata after the Yellow-billed duck native to Africa. To install the new version, please visit the installation guide. The full release notes can be found here. What’s new in 0.9.0 There have been too […]

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DuckDB's AsOf Joins: Fuzzy Temporal Lookups

TLDR: DuckDB supports AsOf Joins – a way to match nearby values. They are especially useful for searching event tables for temporal analytics. Do you have time series data that you want to join, but the timestamps don’t quite match? Or do you want to look up a value that […]

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Even Friendlier SQL with DuckDB

TLDR; DuckDB continues to push the boundaries of SQL syntax to both simplify queries and make more advanced analyses possible. Highlights include dynamic column selection, queries that start with the FROM clause, function chaining, and list comprehensions. We boldly go where no SQL engine has gone before! Who says that […]

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