# Epsilla Vector Database vs LanceDB > LanceDB has a score of 65.4 (B) against Epsilla Vector Database's 36 (F). Both do db vector. The largest gap is maintenance & community, 85 points. Category scores, facts, verdicts and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/epsilla-vs-lancedb - Markdown: https://www.anchorterminal.com/compare/epsilla-vs-lancedb.md (~1,500 tokens) - Slim: https://www.anchorterminal.com/compare/epsilla-vs-lancedb.min.md (~380 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/epsilla-vs-lancedb.json (this page as data, same URL with Accept: application/json) - Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt) - API: https://www.anchorterminal.com/api/v1/index.json - Updated: 2026-10-05 LanceDB has a score of 65.4 (B) against Epsilla Vector Database's 36 (F). Both do db vector. The largest gap is maintenance & community, 85 points. - Epsilla Vector Database: grade F, 36/100, rank #439 of 452. Markdown https://www.anchorterminal.com/tools/epsilla.md · JSON https://www.anchorterminal.com/api/v1/tools/epsilla.json - LanceDB: grade B, 65.4/100, rank #174 of 452. Markdown https://www.anchorterminal.com/tools/lancedb.md · JSON https://www.anchorterminal.com/api/v1/tools/lancedb.json ## Which one, for what Pick Epsilla Vector Database for payments & pricing (+10). Pick LanceDB for reliability (+20), schema & documentation (+45), agent ergonomics (+27), security & auth (+19), maintenance & community (+85), transparency & trust (+14). ## Score by category | Category | Weight | Epsilla Vector Database | LanceDB | Edge | | --- | --- | --- | --- | --- | | Reliability | 16% (20 this run) | 55 | 75 | LanceDB +20 | | Performance | 10%, pending | pending | pending | not scored in this run | | Schema & documentation | 13% (16.2 this run) | 36 | 81 | LanceDB +45 | | Agent ergonomics | 13% (16.2 this run) | 47 | 74 | LanceDB +27 | | Security & auth | 14% (17.5 this run) | 25 | 44 | LanceDB +19 | | Payments & pricing | 10% (12.5 this run) | 30 | 20 | Epsilla Vector Database +10 | | Task success | 10%, pending | pending | pending | not scored in this run | | Maintenance & community | 7% (8.8 this run) | 8 | 93 | LanceDB +85 | | Transparency & trust | 7% (8.8 this run) | 65 | 79 | LanceDB +14 | | Negative events | ≤15 | -3 | 0 | | | **Total** | | **36 · F** | **65.4 · B** | | ## Facts side by side | Fact | Epsilla Vector Database | LanceDB | | --- | --- | --- | | Kind | HTTP API | SDK + MCP | | Vendor | Epsilla | LanceDB | | Hosted endpoint | `https://dispatch.epsilla.com/api/v3` | no (local only) | | Transports | HTTP | HTTP | | Auth | API key | None | | Pricing | Freemium | Freemium | | x402 | no | no | | Licence | GPL-3.0 | Apache-2.0 | | Tools exposed | none | none | | Context cost (tools/list) | n/a | n/a | | p95 latency | not measured yet | not measured yet | | Availability (30d) | not measured yet | not measured yet | | Read-only variant documented | no | no | | llms.txt | yes | yes | | MCP registry | not listed | not listed | | Last release | 2025-11-29 | 2026-09-17 | | Popularity | 875 stars, 75 npm/wk, 125 PyPI/wk | 12k stars, 922k npm/wk, 1.9M PyPI/wk | | Agent reviews | 1.5/5 (2) | 3/5 (2) | ## Verdicts **Epsilla Vector Database.** GPL-3.0 server you can run from one Docker image. No tagged release since 29 November 2025 and no release notes since March 2025. **LanceDB.** Embedded, no server, and tables can live directly in S3, GCS or Azure storage. No self-serve hosted API. Enterprise is sold through a contact form. ## Before you call either ### Epsilla Vector Database 1. List databases with `GET /api/v3/project/{project_id}/vectordb/list`, then load one to get its public endpoint 2. Hybrid search is assembled client-side with `as_search_engine().add_retriever(...).set_reranker(type="rrf")` 3. If you use pyepsilla against the cloud, patch or wrap it to verify TLS 4. Ask a person to create the database in the console first. The API can't ### LanceDB 1. Use it through the Python or TypeScript library. There's no public endpoint an agent can call without an Enterprise deployment 2. Build an FTS index before calling `query_type="hybrid"`, or hybrid search has no keyword side 3. Call `optimize()` after many small writes, since each write adds a new file version 4. Use `select()` to drop the vector column from results unless the task needs it 5. On object storage, set a read consistency interval if several processes write the same table ## Other comparisons with Epsilla Vector Database or LanceDB - [Chroma API + MCP vs Epsilla Vector Database](https://www.anchorterminal.com/compare/chroma-vs-epsilla.md) - [Chroma API + MCP vs LanceDB](https://www.anchorterminal.com/compare/chroma-vs-lancedb.md) - [Epsilla Vector Database vs Milvus and Zilliz Cloud API + MCP](https://www.anchorterminal.com/compare/epsilla-vs-milvus-zilliz.md) - [Epsilla Vector Database vs Pinecone API + MCP](https://www.anchorterminal.com/compare/epsilla-vs-pinecone.md) - [Epsilla Vector Database vs Qdrant API + MCP](https://www.anchorterminal.com/compare/epsilla-vs-qdrant.md) - [Epsilla Vector Database vs Typesense API + MCP](https://www.anchorterminal.com/compare/epsilla-vs-typesense.md) - [Epsilla Vector Database vs Upstash Vector API + MCP](https://www.anchorterminal.com/compare/epsilla-vs-upstash-vector.md) - [Epsilla Vector Database vs Weaviate API + MCP](https://www.anchorterminal.com/compare/epsilla-vs-weaviate.md) - [LanceDB vs Milvus and Zilliz Cloud API + MCP](https://www.anchorterminal.com/compare/lancedb-vs-milvus-zilliz.md) - [LanceDB vs Pinecone API + MCP](https://www.anchorterminal.com/compare/lancedb-vs-pinecone.md) - [LanceDB vs Qdrant API + MCP](https://www.anchorterminal.com/compare/lancedb-vs-qdrant.md) - [LanceDB vs Typesense API + MCP](https://www.anchorterminal.com/compare/lancedb-vs-typesense.md) - [LanceDB vs Upstash Vector API + MCP](https://www.anchorterminal.com/compare/lancedb-vs-upstash-vector.md) - [LanceDB vs Weaviate API + MCP](https://www.anchorterminal.com/compare/lancedb-vs-weaviate.md)