A library for efficient similarity search and clustering of dense vectors.
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Open Source alternative to Algolia + Pinecone and an Easier-to-Use alternative to ElasticSearch ⚡ 🔍 ✨ Fast, typo tolerant, in-memory fuzzy Search Engine for building delightful search experiences
- search-engine
- search
- typo-tolerance
- site-search
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
- search-engine
- semantic-search
- semantic-search-engine
- vector-search
[MLsys2026 Best Paper]: https://arxiv.org/abs/2506.08276. RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.
💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows
- python
- search
- nlp
- semantic-search
Developer-friendly OSS embedded retrieval library for multimodal AI. Search More; Manage Less.
- approximate-nearest-neighbor-search
- image-search
- nearest-neighbor-search
- recommender-system
Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.
A simple, fast and versatile Datalog database
- key-value-store
- embedded-database
- fulltext-search
- vector-database
Embeddable vector database for Go with Chroma-like interface and zero third-party dependencies. In-memory with optional persistence.
- embeddings
- go
- golang
- llm
Embeddable, in-memory, document-oriented database with a high-level Query builder interface.
- database
- embedable
- go
- in-memory
Language model search engine built on a vector database and an anything key/value store.
- information-retrieval
- search-engine
- vector-space-model
- machine-learning
A c++ toolbox of locality-sensitive hashing (LSH), provides several popular LSH algorithms, also support python and matlab.
A convenient data structure supporting efficient in-memory indexing and querying, including range queries, fuzzy string matching and vector search.