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DuckDB is an in-process
SQL OLAP database management system

Why DuckDB?

Simple

  • In-process, serverless
  • C++11, no dependencies, single file build
  • APIs for Python/R/Java/…
more

Feature-rich

  • Transactions, persistence
  • Extensive SQL support
  • Direct Parquet & CSV querying
more

Fast

  • Vectorized engine
  • Optimized for analytics
  • Parallel query processing
more

Free

  • Free & Open Source
  • Permissive MIT License
more

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

When to use DuckDB

  • Processing and storing tabular datasets, e.g. from CSV or Parquet files
  • Interactive data analysis, e.g. Joining & 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

Blog

Archive
2023-05-26

Correlated Subqueries in SQL

Subqueries in SQL are a powerful abstraction that allow simple queries to be used as composable building blocks. They allow you to break down complex problems into smaller parts, and subsequently make it easier to write, understand and maintain large and complex queries. DuckDB uses a state-of-the-art subquery decorrelation optimizer […]

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2023-05-17

Announcing DuckDB 0.8.0

The DuckDB team is happy to announce the latest DuckDB release (0.8.0). This release is named “Fulvigula” after the Mottled Duck (Anas Fulvigula) native to the Gulf of Mexico. To install the new version, please visit the installation guide. The full release notes can be found here. What’s new in […]

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2023-05-12

10 000 Stars on GitHub

Today, DuckDB reached 10 000 stars on GitHub. We would like to pause for a second to express our gratitude to everyone who contributed to DuckDB and of course all its users. When we started working on DuckDB back in 2018, we would have never dreamt of getting this kind […]

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