Serverless vector search: No cold starts. No size limits.
Firebase, Cloudflare Vectorize — convenient but constrained. LanceDB gives you serverless simplicity with petabyte scale and native hybrid search.
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Tomorrow's AI is being built on LanceDB today
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Stop paying document read costs for vector scans
Firestore charges per document read. Vector search scans lots of documents. That math gets expensive fast. LanceDB runs on Cloud Storage at object storage prices with native hybrid search.
Firebase / Firestore
LanceDB
Cost
Per-document read pricing
Object storage. Up to 100x savings.
Scale
Firestore document limits
20 PB largest table. Billions of vectors.
Search
Vector via extension. No hybrid.
Native vector + full-text + SQL hybrid in one query.
Data model
Document-first
Columnar, vector-native with schema evolution.
Best for
Small vector sets in Firebase apps
Vector search at any scale.
Edge vectors are for tiny datasets. LanceDB is for the rest.
Cloudflare Vectorize is great for edge-cached vector lookups on small datasets. When you need real scale and hybrid search, you need a real vector database.
Cloudflare Vectorize
LanceDB
Scale
Edge-optimized, size-limited
20 PB largest table. 20K+ QPS. Billions of vectors.
Architecture
Edge-distributed
Object storage with compute-storage separation.
Search
Basic vector search
Native vector + full-text + SQL hybrid in one query.
Features
Basic vector search
Search, analytics, schema evolution.
Best for
Tiny vector sets at the edge
Production-scale vector workloads.
Talk to Engineering
Or try LanceDB OSS — same code, scales to Cloud.
Schedule a Technical Consultation