DuckDB is a high-performance analytical database system. It is designed to be fast, reliable, portable, and easy to use. DuckDB provides a rich SQL dialect, with support far beyond basic SQL. DuckDB supports arbitrary and nested correlated subqueries, window functions, collations, complex types (arrays, structs, maps), and several extensions designed to make SQL easier to use.
DuckDB is available as a standalone CLI application and has clients for Python, R, Java, Wasm, etc., with deep integrations with packages such as pandas and dplyr.
For more information on using DuckDB, please refer to the DuckDB documentation.
Last Releases
- DuckDB 1.3.0 “Ossivalis”This release of DuckDB is named “Ossivalis” after Bucephala Ossivalis, an ancestor of the Goldeneye duck that lived Millions of years ago. Please also refer to the announcement blog post:… Read more: DuckDB 1.3.0 “Ossivalis”
- v1.2.2 Bugfix ReleaseThis is a bug fix release for various issues discovered after we released 1.2.1. There are no new major features, just bug fixes. Database files created by DuckDB versions all… Read more: v1.2.2 Bugfix Release
- v1.2.1 Bugfix ReleaseThis is a bug fix release for various issues discovered after we released 1.2.0. There are no new major features, just bug fixes. Database files created by DuckDB versions all… Read more: v1.2.1 Bugfix Release
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Common Issues When Installing DuckDB Locally: Solutions and Fixes
Local installations of data tools are a critical part of any data engineer’s workflow. With powerful tools like DuckDB becoming increasingly popular for managing large datasets efficiently, it’s important to address common issues that may arise during installation. These issues can be frustrating, but with the right solutions, they are typically solvable. In this article,…
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DuckDB: A Lightweight Database for Data Professionals
Introduction DuckDB is a high-performance, in-process database system optimized for analytical workloads. Designed to handle vast datasets efficiently, it is often referred to as the “SQLite for analytics.” Its primary purpose is to provide data professionals, particularly those working in data engineering, analysis, and ETL, with a simple yet powerful solution for managing and querying…
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How to Install DuckDB Locally: A Complete Guide
DuckDB, an in-process SQL database, is widely appreciated for its efficiency and simplicity, making it ideal for data analysis and testing workflows. Installing DuckDB locally empowers developers and data engineers to test queries, perform offline analysis, and develop applications in a self-contained environment. This guide walks through the local installation of DuckDB using common methods…
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42.parquet – A Zip Bomb for the Big Data Age
A 42 KB Parquet file can contain over 4 PB of data due to its compression methods. This exploit, similar to a Zip Bomb, highlights the potential dangers of Parquet files and the importance of careful interpretation. DuckDB can read the file, but materializing the entire table would require over 4 PB of memory. Source:…