DuckDB is an in-process analytical database management system designed for online analytical processing. Unlike a conventional client-server database, DuckDB executes queries within the application process.
The database is particularly useful for querying local datasets, analysing files and performing complex aggregations without operating a separate database service.
DuckDB uses a column-oriented, vectorised query execution engine optimised for analytical workloads. It integrates with data science environments and can query external datasets without first importing them into a conventional database.
This is free and open source software.
Key Features
- Supports SQL joins, aggregations, window functions and complex subqueries.
- Provides vectorised query execution and parallel processing.
- Reads Parquet, CSV and JSON files directly through SQL queries.
- Supports nested data types, including lists, structures and maps.
- Includes ACID transactions with multi-version concurrency control.
- Supports persistent single-file databases and in-memory operation.
- Provides efficient integration with Python DataFrames, Pandas, Polars and R.
- Supports extensions for additional data formats, functionality and external services.
- Offers SQL querying of remote data through HTTP and object storage extensions.
- Provides an interactive command-line interface.
- Supports exporting query results to multiple data formats.
- Cross-platform support – runs on Linux, macOS, and Windows.
Website: github.com/duckdb/duckdb
Support:
Developer: DuckDB Foundation
License: MIT License
DuckDB is written in C++ and C. Learn C++ with our recommended free books and free tutorials. Learn C with our recommended free books and free tutorials.
Related Software
| Column-Oriented Databases | |
|---|---|
| MariaDB ColumnStore | Uses a massively parallel distributed data architecture |
| DuckDB | In-process SQL OLAP database management system |
| Druid | High performance, real-time analytics database |
| Databend | Cloud data warehouse |
| ClickHouse | Real-time analytics database management system |
| InfluxDB Core | Scalable datastore for metrics, events, and real-time analytics |
| Doris | Modern data warehouse for real-time analytics |
| VictoriaMetrics | Scalable solution for monitoring and managing time series data |
| StarRocks | High-performance analytical database |
| MonetDB | High performance relational database system for analytics |
| Kudu | Distributed data storage engine |
| QuestDB | High-performance time-series database |
| Pinot | Real-time analytics platform |
| IoTDB | High-performance time-series database |
| GreptimeDB | Cloud-native database |
| CrateDB | Distributed SQL database management |
| Hyrise | Flexible platform for research into relational data management |
Read our verdict in the software roundup.
| Relational Databases | |
|---|---|
| MariaDB | High compatibility with MySQL, ensuring drop-in replacement capability |
| PostgreSQL | Award winning Object-relational database management system |
| MySQL | Multithreaded, multi-user SQL database management system |
| SQLite | Embeddable SQL Database Engine |
| TiDB | Cloud-native, distributed SQL database |
| DuckDB | In-process SQL OLAP database management system |
| Turso | In-process relational database engine |
| YugabyteDB | PostgreSQL-compatible distributed SQL database |
| rqlite | Distributed database built on SQLite |
| MonetDB | High performance relational database system for analytics |
| Dolt | Version-controlled SQL database |
| Firebird | Relational database offering many ANSI SQL features |
| H2 | Relational database management system written in Java |
| HSQLDB | JDBC interface, client-server version, query tool, grid and more |
| CUBRID | Database engine with built-in enterprise grade features |
| Apache Cloudberry | Massively parallel processing database |
| Virtuoso | Data Management with Web Application Server and Web Services |
| Apache Derby | Full-featured relational database implemented entirely in Java |
Read our verdict in the software roundup.
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