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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 0.8.1 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



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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DuckDB ADBC - Zero-Copy data transfer via Arrow Database Connectivity

TLDR: DuckDB has added support for Arrow Database Connectivity (ADBC), an API standard that enables efficient data ingestion and retrieval from database systems, similar to Open Database Connectivity (ODBC) interface. However, unlike ODBC, ADBC specifically caters to the columnar storage model, facilitating fast data transfers between a columnar database and […]

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