Manipulate JSON-like data with NumPy-like idioms.

High-performance Go package to read and write Parquet files

A fast minimal dependency implementation of Apache Parquet

Yosegi is a Schema-less columnar storage format. Provide flexible representation like JSON and efficient reading similar to other columnar storage formats.

Native Dask collection for awkward arrays, and the library to use it.

Columnar type support for Rust

MULLER: A Multimodal Data Lake Format for Collaborative AI Data Workflows

ETL processing toolset with SQL-like language and GIS capabilities, built on core Spark. Extensible and modular. REPL included

Zig implementation of Apache Arrow

what-you-see-is-what-you-do columnar data serialization library for java

Examples for parsing Parquet files with Hardwood

Just my Master thesis about RDF data and columnar formats

An attempt to create a columnar engine inspired by Apache Parquet

An implementation of Apache Arrow in Zig (WIP)

Spiral (SpiralDB) is a multimodal data platform built for the "machine consumer" — frontier AI systems and agents. It unifies video, images, audio, embeddings, point clouds, sensor streams, tables, and text under one query language and coordinate-frame system, serving everything from raw bytes to model-ready tensors at machine-scale throughput for…

Apache Spark based 'Dist' utility to supplement Data Cooker ETL tool

Apache Arrow is a cross-language development platform for in-memory analytics developed by the Apache Software Foundation. It specifies a standardized, language-independent columnar memory format for flat and nested data, organized for efficient analytic operations on modern hardware including CPUs and GPUs.