duckdb

GitHub describes it as DuckDB is an analytical in-process SQL database management system. The repository metadata lists C++ as its primary language. The metadata lists the MIT license. This article stays within the project description and details documented in the GitHub repository README.

GitHub describes it as DuckDB is an analytical in-process SQL database management system. The repository metadata lists C++ as its primary language. The metadata lists the MIT license. The README describes the project this way: 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.

The README section "DuckDB" states: 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.

The README section "Data Import" states: For CSV files and Parquet files, data import is as simple as referencing the file in the FROM clause:

The README section "Development" states: For development, DuckDB requires CMake, Python 3 and a C++17 compliant compiler. In the root directory, run make to compile the sources. For development, use make debug to build a non-optimized debug version. You should run make unit and make allunit to verify that your version works properly after making changes. To test performance, you can run BUILD BENCHMARK=1 BUILD TPCH=1 make and then perform several standard benchmarks from the root directory by executing ./build/release/benchmark/benchmark runner . The details of benchmarks are in our Benchmark Guide.

The repository README is the source for this review. It does not replace a local installation or an independent test.

• Source 1 · Project repository
• Source 2 · README