Lightning-fast open-source search engine with typo-tolerance, semantic hybrid search, and sub-50ms response times.

In-process OLAP SQL database that runs inside your Python, R, or Node.js process — no server required.

Blazing-fast DataFrame library written in Rust with a Python API — handles datasets that don't fit in RAM.

Open-source vector similarity search for PostgreSQL — store and query embeddings directly in your Postgres DB.

Cloud-native open-source vector database built for billion-scale similarity search and AI applications.

Data quality framework for defining, testing, and documenting expectations about your data pipelines.

Open-source vector database with hybrid search, multi-tenancy, and native ML module integrations.

Open-source Python library for building self-maintaining, schema-evolving data pipelines with minimal code.

The leading data framework for LLM apps — 150+ data loaders, RAG pipelines, and agent tools for connecting any data source to any model.

Microsoft's universal document-to-Markdown converter: PDF, DOCX, PPTX, XLSX, HTML, images, audio, and ZIP — all to clean Markdown.

Facebook AI Similarity Search: blazing-fast library for efficient similarity search and clustering of dense vectors.

AI data lake with multimodal tensor storage, vector search, and serverless SQL — stream datasets directly to PyTorch and TensorFlow.

The open-source AI-native vector database — store, query, and filter embeddings with a simple Python API. Perfect for RAG and semantic search.

High-performance vector database with filtering, payload storage, and a REST/gRPC API — built for production AI.

Serverless, embedded vector database built on Lance columnar format — zero-copy, multimodal, no server needed.

Open-source document ingestion library — partition PDFs, HTML, DOCX, and 25+ formats into clean elements for RAG pipelines.