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DuckDB

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DuckDB
Developer(s)DuckDB Labs
Stable release
v1.1.3 / November 4, 2024 (2024-11-04)
Repository
Written inC++
Operating systemCross-platform
TypeColumn-oriented DBMS
RDBMS
LicenseMIT License
Websitewww.duckdb.org

DuckDB is an open-source column-oriented relational database management system (RDBMS).[1] It is designed to provide high performance on complex queries against large databases in embedded configuration,[2] such as combining tables with hundreds of columns and billions of rows. Unlike other embedded databases (for example, SQLite) DuckDB is not focusing on transactional (OLTP) applications and instead is specialized for online analytical processing (OLAP) workloads.[3] The project has over 6 million downloads per month.[4][5][6]

History

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DuckDB was originally developed by Mark Raasveldt and Hannes Mühleisen at the Centrum Wiskunde & Informatica (CWI) in the Netherlands.[2] The project co-founders designed DuckDB to address the need for an in-process OLAP database solution.[7] DuckDB was first released in 2019.[8] DuckDB version 1.0.0 was released on June 3, 2024 under the codename SnowDuck. [9]

Features

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DuckDB uses a vectorized query processing engine.[10] DuckDB is special amongst database management systems because it does not have any external dependencies and can build with just a C++11 compiler.[11] DuckDB also deviates from the traditional client–server model by running inside a host process (it has bindings, for example, for a Python interpreter with the ability to directly place data into NumPy arrays[2]). DuckDB's SQL parser is derived from the pg_query library developed by Lukas Fittl, which is itself derived from PostgreSQL's SQL parser that has been stripped down as much as possible. [12] [13] DuckDB uses a single-file storage format to store data on disk, designed to support efficient scans and bulk updates, appends and deletes. [14]

Comparison

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DuckDB in its OLAP niche does not compete with the traditional DBMS like MSSQL, PostgreSQL and Oracle database. While using SQL for queries, DuckDB targets serverless applications and provides extremely fast responses using Apache Parquet files for storage. These attributes make it a popular choice for large dataset analysis in interactive mode, but certain commenters have indicated that they believe the serverless nature of DuckDB makes it, as a stand alone tool, "not so suitable for enterprise data warehousing".[15]

Commercial use

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DuckDB is used at Facebook, Google, and Airbnb.[16]

DuckDB co-author Mühleisen also runs a support and consultancy firm for the software, DuckDB Labs.[8] The company has chosen not to take venture capital funding, stating "We feel investment would force the project direction towards monetization, and we would much prefer keeping DuckDB open and available for as many people as possible".[6] Another company, MotherDuck, has received $100m funding for its data platform based on DuckDB, with investors including Andreessen Horowitz.[17]

DuckDB Foundation

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The independent non-profit DuckDB Foundation safeguards the long-term maintenance and development of DuckDB. The foundation holds much of the intellectual property of the project and is funded by charitable donations.[18] The DuckDB Foundation's statutes ensure DuckDB remains open-source under the MIT license in perpetuity.[19]

Language support

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In addition to the native C and C++ APIs, DuckDB supports a range of programming languages.

Client APIs
Language Notes Reference
Java The Java API is implemented using JNI.[20] Integration with the Apache Arrow[21] format is provided. [22]
Python The Python API implements support for the Pandas,[23] Apache Arrow[24] and Polars data analysis packages. [25]
Rust The Rust API is distributed as a rust crate that exposes an elegant wrapper over the native C API. [26]
Node.JS Node API [27]
R R API [28]
Julia Julia API [29]
Swift Swift API [30]

References

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  1. ^ "DuckDB Documentation SQL Introduction". Retrieved 2024-11-20.
  2. ^ a b c Kamphuis, Chris (2020). "Graph Databases for Information Retrieval". Advances in Information Retrieval. Lecture Notes in Computer Science. Vol. 12036. Cham: Springer International Publishing. pp. 608–612. doi:10.1007/978-3-030-45442-5_79. ISBN 978-3-030-45441-8. PMC 7148032.
  3. ^ Raasveldt, Mark; Mühleisen, Hannes (2019-06-25). DuckDB: an Embeddable Analytical Database. ACM. pp. 1981–1984. doi:10.1145/3299869.3320212. ISBN 978-1-4503-5643-5.
  4. ^ "PyPi Download Stats". www.pypistats.org. Archived from the original on 2024-08-13. Retrieved 2024-08-13.
  5. ^ "DuckDB Python Downloads Dashboard". duckdbstats.com. Archived from the original on 2024-08-13. Retrieved 2024-08-13.
  6. ^ a b Clark, Lindsay. "DuckDB Labs puts limit on free support, rules out VC funding". www.theregister.com. Archived from the original on 2024-03-23. Retrieved 2024-03-23.
  7. ^ van der Ent, Leendert (April 2023). "DuckDB: Introducing a New Class of Data Management Systems" (PDF). I/O Magazine. ICT Research Platform Nederland. Retrieved 12 November 2024.
  8. ^ a b Clark, Lindsay. "DuckDB reaches version 0.5.0". www.theregister.com. Archived from the original on 2024-03-07. Retrieved 2024-03-23.
  9. ^ Raasveldt, Mark; Mühleisen, Hannes (3 June 2024). "Announcing DuckDB 1.0.0". Retrieved 12 November 2024.
  10. ^ Raasveldt, Mark; Mühleisen, Hannes (2019-06-25). DuckDB: an Embeddable Analytical Database. ACM. pp. 1981–1984. doi:10.1145/3299869.3320212. ISBN 978-1-4503-5643-5.
  11. ^ "DuckDB Building Instructions". Retrieved 2024-08-16.
  12. ^ Raasveldt, Mark; Mühleisen, Hannes (2019-06-25). DuckDB: an Embeddable Analytical Database. ACM. pp. 1981–1984. doi:10.1145/3299869.3320212. ISBN 978-1-4503-5643-5.
  13. ^ Slot, Marco (24 May 2024). "How We Fused DuckDB into Postgres with Crunchy Bridge for Analytics". Retrieved 12 November 2024.
  14. ^ Raasveldt, Mark; Mühleisen, Hannes (2020). Data Management for Data Science Towards Embedded Analytics (PDF). Conference on Innovative Data Systems Research.
  15. ^ Bannert, M. (2024). Research Software Engineering: A Guide to the Open Source Ecosystem. Chapman & Hall/CRC Data Science Series. CRC Press. p. 25. ISBN 978-1-04-000513-2. Archived from the original on 2024-03-23. Retrieved 2024-03-23.
  16. ^ Clark, Lindsay. "Scale-up database wrangler MotherDuck scores $47.5 million". www.theregister.com. Archived from the original on 2024-03-23. Retrieved 2024-03-23.
  17. ^ Clark, Lindsay. "MotherDuck serverless analytics platform wins $52.5M funding". www.theregister.com. Archived from the original on 2024-03-23. Retrieved 2024-03-23.
  18. ^ "DuckDB Foundation". Retrieved 2024-11-09.
  19. ^ "DuckDB Project FAQs". Retrieved 2024-11-09.
  20. ^ "Java JNI Source Code". www.github.com. Retrieved 2024-09-07.
  21. ^ "DuckDB Java Arrow Source Code". www.github.com. Retrieved 2024-09-07.
  22. ^ "DuckDB Java Source Code". www.github.com. Retrieved 2024-09-07.
  23. ^ "DuckDB Pandas Source". www.github.com. Retrieved 2024-09-07.
  24. ^ "DuckDB PyArrow Source". www.github.com. Retrieved 2024-09-07.
  25. ^ "DuckDB Python Source Code". www.github.com. Retrieved 2024-09-07.
  26. ^ "DuckDB Rust Source Code". www.github.com. Retrieved 2024-09-07.
  27. ^ "DuckDB Node Source Code". www.github.com. Retrieved 2024-09-07.
  28. ^ "DuckDB R Source Code". www.github.com. Retrieved 2024-09-07.
  29. ^ "DuckDB Jullia Source Code". www.github.com. Retrieved 2024-09-07.
  30. ^ "DuckDB Swift Source Code". www.github.com. Retrieved 2024-09-07.

Further reading

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