Create full-fledged APIs for slowly moving datasets without writing a single line of code.

New and extensible file format for storage of large columnar datasets.

Copy to/from Parquet in S3, Azure Blob Storage, Google Cloud Storage, http(s) stores, local files or standard inout stream from within PostgreSQL

DuckDB-powered data lake analytics from Postgres

Parse, view, query, edit, and export IFC, IDS, BCF, pointclouds and more AEC stuff. In the browser, server or desktop.

Manipulate arrays of complex data structures as easily as Numpy.

SIMD-accelerated columnar database for analytics — pure C, zero dependencies

Document, columnar, KV, Graph, Vector, Array - The only all-in-one database that you need.

🧊 A curated list of OLAP databases, data lake tools, columnar engines, and analytics frameworks for data engineers.

Graph database native to the cloud. Embedded, multi-tenant, built on object storage.

Fast, minimal, and ergonomic zero-copy Apache Arrow tabular data implementation in Rust, with PyO3, Python bindings, shared-memory and low-latency SIMD for data-engineering and columnar workloads. Bridge to Polars and Arrow-rs over FFI effortlessly.

C-Store : A column-oriented DBMS prototype (frozen)

In-memory, columnar, arrow-based database.

Uni is a modern, embedded database that combines property graph (OpenCypher), vector search, and columnar storage (Lance) into a single, cohesive engine. It is designed for applications requiring local, fast, and multimodal data access, backed by object storage (S3/GCS) durability.

Backend for columnar, fully orchestrated HEP analyses with pure Python, law and order.

ergonomic columnar storage encoding crate

Columnar type support for Rust

Quick Data Format — fast, compact binary serialization for Go. encoding/json-style API, columnar per-column codecs, up to 68% smaller than Protobuf.

Quick, easy and pretty display of tabular data or matrices, with optional ANSI color and borders

Full-stack performance engineering handbook — Linux kernel & eBPF, profiling/tracing, network & JVM/GPU tuning, storage engines, databases, distributed systems and streaming/ML data architectures, plus the high-performance data structures behind them: probabilistic sketches, vector/ANN indexes, columnar encoding, LSM & learned indexes, HFT C++.