Open Source Search Apps

Open-source vector database and search engine built in Rust for production-grade AI applications — from semantic search to RAG pipelines and recommendation systems.

An open-source, C++ search database positioned as a faster, lighter alternative to Elasticsearch — supporting full-text, SQL, JSON, and vector/embedding search over a MySQL-compatible protocol.

Open-source vector database combining semantic search, hybrid queries, RAG, and image search in a single cloud-native system built for production scale.

Lightning-fast hybrid search engine with AI-powered semantic and full-text retrieval for modern applications.

The open-source Postgres development platform that replaces Firebase with authentication, real-time APIs, edge functions, storage, and vector embeddings — all built on PostgreSQL.

Born out of Y Combinator's S2023 batch, ParadeDB is a Postgres extension that delivers Elasticsearch-quality BM25 search and real-time analytics without a separate search cluster to manage.

Cloud-native search engine for logs and traces, delivering sub-second search directly on S3, GCS, or Azure Blob storage at a fraction of Elasticsearch's cost.

Fast, lightweight, schema-less search backend in Rust — microsecond queries, 30MB RAM, no document storage required.

The open-source, unlimited NotebookLM alternative with real-time collaboration, a desktop app, and no vendor lock-in.

A self-hosted, AI-powered code search engine that indexes every repo across GitHub, GitLab, Bitbucket, Gitea, Gerrit, and Azure DevOps, so both engineers and coding agents can search, browse, and ask questions about your codebase from one place.

A blazing-fast, typo-tolerant open-source search engine that delivers instant search experiences with built-in vector, semantic, and geo-search — all from a single binary.

Privacy-first metasearch engine that aggregates results from 250+ search services — no tracking, no profiling, full control when self-hosted.

Morphik is an AI-native ingestion and retrieval engine that lets developers store, search, and reason over visually rich documents — scanned PDFs, manuals, slides, and video — without duct-taping together OCR, an embedding model, and a vector database.

A complete, embeddable search engine and RAG pipeline running in browsers, servers, and edge networks with full-text, vector, and hybrid search in under 2KB.

Federated AI search and RAG across 100+ enterprise sources—no data extraction, no vector database required.