Tags: #vector-search

An open lakehouse format designed for multimodal AI, offering high-performance vector search, lightning-fast random access, and robust data versioning capabilities.

Qdrant is a high-performance, massive-scale vector database and search engine designed for next-generation AI applications.

An open-source, embedded retrieval library and multimodal AI lakehouse designed for fast, scalable vector search and data management in AI/ML applications.

A Redis module that provides advanced querying, secondary indexing, full-text search, vector similarity search, and aggregations for Redis data.

A unified, open-source enterprise data warehouse built in Rust, offering analytics, vector search, and full-text search, specifically designed for AI agents with secure Python UDF sandboxes.

A high-performance, continuously available, and transparently scalable distributed relational database supporting transactional, analytical, and AI workloads with MySQL compatibility.

A tiny, versatile JavaScript search engine offering full-text, vector, and hybrid search with RAG capabilities for browser, server, and edge.

Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data, always in sync with various data sources.

An all-in-one API platform providing advanced search, recommendations, and Retrieval-Augmented Generation (RAG) capabilities for developers.

Morphik Core is an AI-native platform providing accurate document search and storage for building robust AI applications, specifically designed to handle complex, visually rich, and multimodal data, overcoming the limitations of traditional RAG.

A scalable, low-latency PostgreSQL extension written in Rust, enabling advanced vector similarity search directly within your relational database.

Typesense is a fast, open-source, typo-tolerant search engine designed to deliver delightful search experiences, serving as an easier-to-use alternative to ElasticSearch and a powerful alternative to Algolia and Pinecone.