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/…
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Feature-rich

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

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

  • Free & Open Source
  • Permissive MIT License
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All the benefits of a database, none of the hassle.

Installation

Choose your environment to use for DuckDB

  • Python
  • R
  • Java
  • node.js
  • C++
  • CLI
pip install duckdb==0.2.5

Latest release: DuckDB 0.2.5 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. 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

  • Non-rectangular data sets, e.g. graphs, plaintext
  • 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