Self-Hosted Vector Databases
As of June 2026, AIDiveForge tracks 4 self-hosted vector databases. Curated self-hosted vector databases tracked by AIDiveForge. Listings are verified against each tool's live website and re-checked regularly.
Last updated June 18, 2026 · 4 tools
1. debate.tellodb
The core mechanism is fact supersession: when a user moves from NYC to SF, TelloDB marks the old location as stale and filters it from active agent context — so the LLM never hallucinates a two-year-old truth. A hybrid HNSW vector plus BM25 search index handles recall, while a separate Metric Vault layer resolves numeric queries deterministically before they ever reach the LLM. The vendor reports p99 retrieval at 4.2ms and benchmarks recall precision above 95% on LongMemEval-S against 68% for standard RAG. The engine ships as a single Rust binary, self-hostable or deployable on the vendor's platform. At v0.1.0, the surface area is narrow — this is a memory layer, not a full agent runtime.
Paid
2. GalaxDB
The core bet is that keeping structured rows, dense embeddings, JSON, blobs, and training snapshots in one storage engine eliminates the synchronization failures that happen when each lives somewhere else. You declare an EMBEDDING MODEL in your DDL and every INSERT triggers a local sidecar that computes and indexes the vector — no Airflow, no Lambda, no external API call. Time-travel lets you tag a snapshot before a training run and replay the exact data the model saw months later, which means reproducibility stops being a manual discipline. The ceiling appears at scale: v1.0-beta.1 benchmarks are real but the project is pre-GA, and teams running serious production traffic will be betting on a single vendor with no public track record at that load. If your stack already runs on managed Postgres and a mature vector service, the migration cost has to pencil out against the consolidation savings.
Paid
3. LanceDB
Open-source embedded vector database for multimodal AI with billion-scale search on Lance columnar format.
Paid
4. SynapCores
The engine handles graph traversal, HNSW vector similarity, and in-database LLM inference inside a single MATCH statement, so the four-to-five round-trips that Pinecone plus Postgres plus an external reranker produce become one. The Community Edition ships with 161 ready-to-run recipes covering GraphRAG, fraud detection, document ingestion, and AutoML — each a runnable markdown file you can modify locally. The ceiling arrives at the infrastructure layer: multi-node clustering, Raft replication, and CDC ingest from MySQL or Postgres binlogs are paid-only features. Teams that outgrow a single host hit that wall before they hit a query performance problem. For single-host deployments, the binary wire protocol and B-tree indexes the vendor targets in a future release are not yet available.
Paid
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