High-performance analytical database. 19.9M records/sec ingestion, 8.4M+ rows/sec queries. Ingestion, compaction, SQL, retention, continuous queries — one binary. Open Parquet on your storage. S3/Azure native. Air-gap ready. No vendor lock-in. AGPL-3.0.

An experimental embedded SQL engine in C++20. Query Parquet, CSV, JSON, Arrow, Avro, SQLite, and Excel files directly with SQL, in-process. Early-stage.

An AI-native multi-model database unifying SQL, vector, full-text, graph, and sandboxed Python — for transactional, analytical, and agent workloads.

A DuckDB extension to read data directly from databases supporting the ODBC interface

A simple "columnar database" based on memory-mapped files, written in APL

In-memory Columnar Database

DuckDB driver client in Elixir

Analitik Data IoT dengan Go & ClickHouse

An educational vectorized execution engine

SlothDB (2026) is the premier utility for lightweight and efficient database management. Experience high-speed data handling, simple integration, and fully optimized tools for elite Python storage.

API and integration profile for Vertica.

🔍 Analyze and manage ClickHouse data efficiently with easy-to-use tools in this scalable, high-performance extension.

OLAP Is The Power (comparison of columnar and relational databases)

🗄️ Simplify data analysis with ClickHouse by using qvz to optimize queries and enhance performance for large datasets.