If you're building a RAG pipeline, a semantic search feature, or anything that needs to store and query embeddings at scale, you've probably run into both of these names. In plain terms: a vector database lets your app find "things similar to this" — the article most like the one you're reading, the support ticket closest to a new one, the code snippet closest to your query — instead of only matching exact keywords. turbopuffer and LanceDB both chase the same idea (store vectors on cheap object storage like S3 instead of expensive dedicated servers), but they land in very different places on price, control and maturity.
The short version: turbopuffer is a paid, fully-managed service already running in production at Cursor, Notion and Linear, with no free tier. LanceDB is a free, open-source, self-hostable database with real adoption at Netflix, Uber and Databricks, plus a paid cloud tier for teams that don't want to run it themselves. If you want something to just work without touching infrastructure and you're fine paying from day one, turbopuffer wins. If you want a free, embeddable, self-hosted option — or you need SOC 2/HIPAA compliance out of the box — LanceDB wins.
turbopuffer
turbopuffer is a vector and full-text search database built directly on object storage, aimed at teams that want production-grade hybrid search (vector + BM25 keyword search combined) without running their own cluster.
Price: Usage-based, no free tier at all. Launch starts at $16/month, Scale at $256/month, Enterprise at $4,096/month (which includes a 99.95% SLA).
Strengths: the object-storage architecture makes it meaningfully cheaper at scale than dedicated-server rivals like Pinecone; sub-10ms p50 latency with true hybrid vector + BM25 search in one query; real production references at serious scale — Cursor, Notion, Linear and Anthropic all run on it.
Limits: nothing to try for free — you need a credit card and $16/month minimum just to start; closed source, no self-hosting option at all, so you're fully dependent on their infrastructure and pricing.
LanceDB
LanceDB is an open-source database purpose-built to store and search the large piles of images, text and embeddings that AI systems train on and retrieve from — including vector search, full-text search, hybrid search and native SQL filters in one engine.
Price: The core is free and open-source (Apache 2.0), so you can self-host it at zero licensing cost. LanceDB Cloud and Enterprise pricing isn't published — you talk to sales for the managed version.
Strengths: 11,000+ GitHub stars and genuine production adoption at Netflix, Uber, Runway, Databricks and ByteDance; a $30M Series A means it's well-funded and unlikely to disappear; free, embeddable, self-hostable Apache 2.0 core; handles vector, full-text and hybrid search plus SQL filters natively, not as an add-on; SOC 2, GDPR and HIPAA certified.
Limits: if you want the managed cloud version, pricing isn't public and you'll need a sales conversation; it can be overkill if you just need simple vector search rather than a full data lakehouse; the managed cloud offering has a shorter track record than turbopuffer's or Pinecone's hosted services; you'll need to get familiar with the Lance file format to use it well.
Side-by-side
| turbopuffer | LanceDB | |
|---|---|---|
| Model | Closed-source, managed only | Open-source core (Apache 2.0), self-host or managed cloud |
| Price | From $16/mo, no free tier | Free (self-hosted core); Cloud/Enterprise on quote |
| Latency | Sub-10ms p50, hybrid vector+BM25 | Fast, plus native SQL filters and full-text |
| Compliance | Not specified publicly | SOC 2, GDPR, HIPAA certified |
| Notable users | Cursor, Notion, Linear, Anthropic | Netflix, Uber, Runway, Databricks, ByteDance |
| Self-hosting | Not available | Yes, from the open-source core |
Verdict
Pick turbopuffer if: you want a managed service with a proven low-latency track record at real production scale, you're comfortable paying from the first dollar, and you don't need to self-host or hit a specific compliance certification turbopuffer doesn't publicly list.
Pick LanceDB if: you want to start for free and self-host, you need SOC 2/GDPR/HIPAA compliance out of the box, you want vector search bundled with SQL filters and full-text search in one open-source engine, or you're not ready to commit to a paid managed vendor before you've validated your use case.
Both are reasonable defaults for a RAG or semantic search stack in 2026 — the honest dividing line is less about raw performance (both are fast enough for the vast majority of workloads) and more about whether you want to own your infrastructure or hand it off entirely.