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

String compression library for database engines: per-row random access and predicate evaluation on the compressed stream.

In-memory columnar query engine for TypeScript with low memory usage, explicit indexes, and fast filtering

Filesystem-native analytical tables you can actually read. Each table is plain Parquet plus JSON files you can open with everyday tools, with a fast SQL engine on top: row-level edits (delete, update, merge), near-instant repeat queries, full table history with time travel, and optional encryption. Built in Rust.