Databases

A Python library for migrating a vector index to a new embedding model progressively, serving search from the existing index while target vectors are computed and cached in the background, instead of re-embedding the whole corpus before the new model can serve any traffic.

• RAG
• Databases

An embedded vector database for multi-agent memory that branches a base vector index in about half a millisecond using copy-on-write, instead of fully copying the index to snapshot, fork or checkpoint it as other vector stores require.

• Agent memory
• Databases

A vector similarity search engine written in Rust that compiles to a 54 KB WebAssembly module, letting a web application run semantic search entirely in the browser with sub-millisecond query latency and no server, API key or per-query cost.

• RAG
• Databases

A shared memory system that lets multiple AI agents, such as Claude Code running on different machines, store and recall facts, decisions and status through one Postgres-backed store.

• Agent memory
• Databases

The official LangChain integration package for the Milvus vector database, providing vector storage, similarity search, hybrid search and retrieval-augmented generation support.

• RAG
• Databases

A self-hosted memory database for AI applications, combining Postgres and pgvector with hybrid search and a knowledge graph so decisions and context persist across sessions with an AI assistant.

• Agent memory
• Databases

A Python library that integrates embedding and reranker models from providers such as OpenAI, Voyage AI, Cohere and Hugging Face for use with the Milvus vector database.

• RAG
• Databases

A community-maintained knowledge base of ClickHouse solutions and troubleshooting notes, written by Altinity engineers and the ClickHouse community and published as a searchable website.

• Databases
• Documentation tools

A Dart-based data engine that combines relational tables with vector and unstructured data, offering ACID transactions, joins, aggregations and hybrid vector retrieval for mobile, desktop, server and edge deployments.

• Databases

A Python SDK for building vector search, retrieval-augmented generation and AI applications directly on Oracle AI Database, combining semantic similarity with relational and spatial filtering.

• RAG
• Databases

A SQL toolchain that compiles annotated .sql files into type-safe database access code for ten languages and ten databases, with linting, security auditing and pre-commit hooks.

• Code quality
• Databases

A research query engine that uses a pipeline of LLM agents to generate instance-optimized, standalone executable code for SQL queries, tailored to a specific dataset, workload and hardware.

• Databases

A local search engine that indexes images, video and other hard-to-search files using OCR, speech-to-text, image embeddings and automated tagging, letting several models' results sit side by side at search time.

• RAG
• Databases

An embedded vector database for larger-than-memory search and analytics on billion-scale multimodal data, using Parquet storage with Arrow-native execution.

• Databases

A memory system for AI agents that pairs vector search with a temporal knowledge graph and a background process that consolidates memories, flags contradictions and lets unused facts fade over time.

• Agent memory
• Databases

An embedded retrieval library that runs full-text, vector, hybrid and SQL search over one table, stored as ordinary Parquet files on local disk or object storage.

• RAG
• Databases

An execution engine that runs SQL extended with natural-language operators, so a query can ask a language model to evaluate a condition on every row instead of filtering only on structured columns.

• Databases
• Data engineering

A local, offline question-answering system built on retrieval-augmented generation, demonstrated on logistics-industry documents but built to be repointed at any organization's own knowledge base.

• RAG
• Databases

A TypeScript walkthrough demo showing how to build semantic search over a CSV dataset using the Pinecone vector database and a sentence-transformers embedding model.

• Databases
• Tutorials

The source for the public website that documents the Weaviate vector database, built with the Docusaurus static site generator.

• Databases
• Documentation tools

An embeddable vector database with document storage, hybrid search, and metadata filtering, designed to scale beyond available memory without running as a separate server.

• Databases

An AST-powered code intelligence engine that indexes a codebase into a persistent knowledge graph with Cypher queries, cross-file call resolution and hybrid semantic search across 62 languages.

• Agent memory
• Databases

A local-first memory engine for AI agents that fuses vector, graph, and columnar storage under one query language, and can explain the evidence behind each recall.

• Agent memory
• Databases

A high-performance knowledge graph engine built for LLMs, GraphRAG and AI-native applications, using sparse matrix algebra for sub-millisecond graph traversals and full OpenCypher query support.

• RAG
• Databases