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Glossary

What is semantic search?

Semantic search finds results by meaning rather than exact keywords, comparing embeddings of the query and documents to surface conceptually similar matches.

Instead of matching literal words, semantic search embeds the query and the corpus into vectors and returns the nearest neighbours. That handles synonyms and paraphrase, and is the retrieval step behind most RAG systems.

In practice it is often combined with traditional keyword search — a hybrid approach — to get both conceptual recall and exact-term precision. Open-source vector databases provide the index that makes it fast.

Best vector databases

Trending semantic search projects

  1. topoteretes/cognee

    Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory across sessions with a self-hosted knowledge graph engine.

    28.2K+180 · 24hmomentum 37Python
  2. redis/redis

    For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.

    75.6K+23 · 24hmomentum 31C
  3. infiniflow/ragflow

    RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs

    85.3K+42 · 24hmomentum 29Go
  4. milvus-io/milvus

    Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search

    45.3K+9 · 24hmomentum 28Go
  5. Tencent/WeKnora

    Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.

    18.5K+28 · 24hmomentum 28Go
  6. qdrant/qdrant

    Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

    33.4K+26 · 24hmomentum 27Rust
  7. lancedb/lancedb

    Developer-friendly OSS embedded retrieval library for multimodal AI. Search More; Manage Less.

    10.9K+6 · 24hmomentum 27HTML
  8. cocoindex-io/cocoindex

    Incremental engine for long horizon agents 🌟 Star if you like it!

    10.9K+55 · 24hmomentum 25Rust

semantic search — FAQ

What is semantic search?
Semantic search finds results by meaning rather than exact keywords, comparing embeddings of the query and documents to surface conceptually similar matches. Instead of matching literal words, semantic search embeds the query and the corpus into vectors and returns the nearest neighbours. That handles synonyms and paraphrase, and is the retrieval step behind most RAG systems.