The Managed LanceDB Vector Database

If you want a production database for RAG, agents, and multimodal search that can handle large-scale traffic, tight latency budgets, and growing datasets (without blowing up your cloud bill), use LanceDB Enterprise as your storage + retrieval layer.

LanceDB is an AI-native vector database built on the open Lance columnar format for multimodal data (text, images, video, embeddings, and features). Under the hood, Lance is optimized for fast random access with techniques like shuffling and column pruning.

LanceDB Enterprise runs this stack as a serverless service: capacity scales with load, storage stays efficient, and you’re not maintaining yet another cluster just to keep retrieval online.

Why Upgrade to LanceDB Enterprise?

LanceDB Enterprise is for teams that want the LanceDB vector database as part of a production platform, not a one-off deployment. The emphasis is on predictable performance and cost, with less operational overhead.

• Performance and scale
  LanceDB Enterprise runs as a serverless service. When traffic is low, capacity scales down; when traffic spikes, it scales up. You avoid the usual pattern of over-provisioned nodes sitting idle “just in case.”

• Compute and storage separation
  Data is stored in Lance, an open-source efficient columnar format that integrates with your existing data lake or S3 compatible object store. Query services scale independently. In practice, that means fewer high-RAM instances and replicas to hit your latency targets, which keeps the LanceDB vector database cheaper to run at a given workload.

• Managed operations
  Backups, upgrades, compaction, and index maintenance are handled by the platform. You still control how LanceDB Enterprise fits into your environment, but the routine work needed to keep a managed vector database healthy is handled for you.

Overall, LanceDB Enterprise is there so you can treat the LanceDB vector database like any other core service: serverless where it makes sense, cost-aware by design, and not something engineers are constantly babysitting.

Enterprise-Grade Vector Search

LanceDB Enterprise adds the deployment and networking options you’d expect from an enterprise platform.

• Support for VPC peering and private connectivity
• Regional deployment choices to match data residency requirements
• SLAs for uptime and performance around vector search workloads

Get enterprise-grade latency, availability, and isolation without maintaining a custom platform or over-sizing hardware to feel safe.

Trusted by Industry Leaders

“LanceDB has been an incredibly useful tool in Character.ai’s petabyte scale Data Lake. The combination of a fast vector search with the tight integrations with the rest of our tooling means we can iterate quickly and efficiently. We appreciate the flexibility and versatility of LanceDB. With Lance we can use the same tooling to store heterogeneous types of data, serve searches and accelerate machine learning workflows in a scalable and extensible way.”
- Ryan Vilim, Member of Technical Staff, Character.ai

Fully Compatible with LanceDB Python

LanceDB Enterprise is designed to work with the same clients and workflows you’d use for local or self-hosted deployments.

• Existing applications built on LanceDB Python, Node, or Rust can be directed at the managed service with minimal changes
• Data models and schemas carry over, since the same storage format and query model are used
• Teams can keep their current development patterns while shifting uptime, scaling, and cost management to the platform

The idea is to make the move from “LanceDB Python in a notebook or service” to “LanceDB Enterprise in production” a configuration change, not a rewrite. Because LanceDB Enterprise uses the same open Lance format, your data stays portable, the same tables work in embedded mode, your VPC, or the managed service.

Get Started with LanceDB

LanceDB Enterprise provides:

• An AI-native multimodal database with a built-in LanceDB vector database
• A serverless operating model that reduces idle capacity and keeps costs predictable
• Managed operations and enterprise features so you can rely on it in production