The Native S3 Vector Database

LanceDB runs vector search directly on S3. Store Lance tables in your own buckets. S3 is the storage layer and source of truth. Reduce costs by up to 200x while serving millions of tables and tens of billions of rows.

Why teams switch

Compute-storage separation

Storage on object storage. Compute scales independently. Query services scale up, down, or to zero.

One table, not six systems

Blobs, embeddings, and metadata stored together in Lance tables on S3. No separate vector index to sync.

Schema evolution without rebuilds

New features are appends, not migrations. No full table rewrites.

Full-text + hybrid search, native

Vector, full-text, and SQL queries in one system. Built for S3, not bolted on.

Comparison

	Traditional Vector DB + S3	LanceDB
Cost	Duplicate storage - S3 for blobs + vector DB for embeddings.	Single storage layer on S3. Up to 100x savings.
Scale	Vector DB limited by RAM. S3 unlimited but needs ETL.	20 PB largest table. Direct S3 access. No ETL.
Search	Vector DB for similarity. S3 needs separate retrieval.	Native vector, full-text, and SQL hybrid on S3 data.
Data model	Vector DB has embeddings. S3 has blobs. Sync required.	Raw data, embeddings, and features in one table on S3.
Purpose	Separate systems for storage and search.	Unified storage and search on your object storage.
Best for	Traditional workloads with separate blob storage.	S3-native vector workloads at scale.

The Power of the Lance Format

Vector Search

Fast scans and random access from the same table — no tradeoff
Zero-copy access for high throughput without serialization overhead

Multi-Modal

Raw data, embeddings, and metadata in one table — not pointers to blob storage
No separate metadata store to keep in sync

Enterprise-Grade Requirements

Security

Granular RBAC, SSO integration, and VPC deployment options.

Governance

Data versioning and time-travel capabilities for auditability.

Support

Dedicated technical account management and guaranteed SLAs.