Multimodal Vector Database for Image, Video & Text
LanceDB keeps images, video, audio, text, metadata, and embeddings in one engine. Stop wiring together SQL databases and separate layers for embeddings and blobs. LanceDB collocates everything - simpler governance, less I/O, better performance.
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Why teams switch
Compute-storage separation
Storage on object storage. Compute scales independently. Up to 100x savings vs RAM-bound architectures.
One table, not six systems
Images, video, audio, text, metadata, and embeddings in one table. No sync jobs, no pointer-chasing.
Schema evolution without rebuilds
Add embedding columns as models improve. No re-indexing, no migrations, no downtime.
Full-text + hybrid search, native
Dense vectors, sparse vectors, and keyword scores in one query.
Comparison
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.
Talk to Engineering
Or try LanceDB OSS — same code, scales to Cloud.
