ChromaOpen-source embedding database for building AI apps with retrieval.
Why switchChroma is an embedding database: point RAG at it and get vector search. LatticeDB is one embedded file where vector search, BM25 and graph traversal compose in a single query. Pick Chroma for pure similarity at scale with an ecosystem behind it; pick LatticeDB when the edges between chunks are load-bearing.
Full comparison → helix-dbRust OLTP graph database on object storage with native vector and BM25 search: property graph, traversal-prefiltered ANN and full-text in one transactional engine; Rust, TS, Go, Python SDKs.
Why switchSame bet: traversal, vector ANN and BM25 in one engine for Graph RAG and agent memory. latticedb is an embedded single-file Zig library; HelixDB runs as a server or embedded on object storage with four SDKs.
Full comparison → pgGraphPostgreSQL extension adding graph search, traversal and shortest-path over your existing tables — a derived graph index queried from plain SQL, no separate graph DB or query language. Rust.
Why switchBoth refuse to run a separate graph server. Pggraph adds graph search and traversal to the Postgres tables you already have, queried in plain SQL; LatticeDB is a zero-config single file with its own engine and query layer for one local process.
Full comparison → hydradbObject-store-native distributed graph DB in Rust: graph on SlateDB over S3, snapshot-consistent OpenCypher, GraphBLAS traversal, Neo4j Bolt 5.x compatibility, disaggregated data nodes and indexers.
Why switchOpposite ends of the same need: latticedb is an embedded single-file graph+vector+BM25 store, hydradb is a distributed S3-backed cluster — pick by whether the graph outgrows one process.
Full comparison → turbovecRust vector index with Python bindings built on Google's TurboQuant: no training step, online ingest, hand-written SIMD kernels — 10M x 1536 vectors in ~4 GB, with allowlist-filtered search.
Why switchBoth embed search with no server to run. LatticeDB fuses graph traversal, HNSW and BM25 into one query language in a single file; turbovec does one thing — quantized dense search — and expects another system to handle the rest.
Full comparison →