MongoDB Atlas alternative. Let MongoDB handle documents. Let LanceDB handle vectors.
Evaluating MongoDB Atlas vector search? LanceDB is purpose-built for vector workloads.
Tomorrow's AI is being built on LanceDB today
Why teams switch
Compute-storage separation
Dedicated vector infrastructure on object storage. No document database markup. Up to 100x savings.
One table, not six systems
Raw data, embeddings, and features together. No sync jobs between MongoDB and a separate vector index.
Schema evolution without rebuilds
New embedding model? Add a column. No document migrations, no re-indexing.
Full-text + hybrid search, native
Vector, full-text, and SQL queries in one system. Purpose-built, not bolted on.
Comparison
| MongoDB Atlas | LanceDB | |
|---|---|---|
| Cost | MongoDB vector search adds vectors to document model—three paradigms to manage. | Dedicated object storage with compute-storage separation. Up to 100x savings. |
| Scale | Vector capabilities within broader document DB architecture. | 20 PB largest table. 20K+ QPS. Billions of vectors. |
| Search | Vector search + Atlas Search (Lucene-based). | Native vector, full-text, and SQL hybrid search in one query. |
| Data model | Document-first architecture. | Schema evolution - raw data, embeddings, and features in one table. |
| Purpose | General-purpose document store with vector features. | Purpose-built for vector and AI workloads. |
| Best for | Document-heavy apps adding simple vector search. | Vector-first 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.
Talk to Engineering
Or try LanceDB OSS — same code, scales to Cloud.