#vector-search
Open source repositories tagged with #vector-search, ranked by health score.
XERJ is the new way for AI to search data. Its autoindex capability activates agents to know your data without the token waste of grep and sed. One command indexes code, docs, logs and PDFs for search, RAG, security audits and agent memory, using 40x fewer tokens than grep. Elasticsearch compatible, so existing clients just work.
The Fastest Distributed Database for Transactional, Analytical, and AI Workloads.
SeekStorm: vector & lexical search - in-process library & multi-tenancy server, in Rust.
High-performance AI memory retrieval for local agent history — a Rust search core (SDK / API / JSON CLI) plus a desktop GUI. Tantivy + Jieba keyword search, optional semantic recall, stable Turn/Run/Session/Project IDs.
One Postgres for your application data, full-text search, vector retrieval, and aggregations. Home of the pg_search extension.
The AI search platform
Shared Single-file memory layer for all your agents, sub mili-second RAG over text, photo and video on Apple Silicon.. No Server. No API. One File. Pure Swift
ArcadeDB Multi-Model Database, one DBMS that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB and Redis. ArcadeDB is a conceptual fork of OrientDB, the first Multi-Model DBMS. ArcadeDB supports Vector Embeddings.
Persistent, encrypted memory for AI agents: one Rust binary, one file, no cloud. 122 canonical MCP tools, hybrid recall, bi-temporal history, AES-256-GCM. Local-first, air-gap ready, MIT.
Cognitive memory backbone for AI agents. Biologically-inspired 4-tier memory, it remembers, forgets, consolidates, and forms associations across a memory graph — Hebbian co-activation, temporal chains, and entity links.