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Brendan Clement
486f6c66bb
This PR is part of the documentation revamp. Once the full set of PRs is merged, we’ll publish the combined site to staging for review before updating docs.lancedb.com. The introductory pages are inconsistent, and the old PR split asked reviewers to review some pages twice. This brings the final quickstart, connection guide, architecture and Concepts pages together. It clarifies OSS and Enterprise, simplifies naming rules and includes the navigation and diagram fixes from #4489. Function and Secret details on the Concepts pages are MDX comments until their release, and CONTRIBUTING.md explains how to write docs before a release. Includes #4532. Ingestion, search and integrations are in #4533; data workflows, SQL and operations are in #4534. Each MDX file has one PR owner. Local assembly, Mint validation and link checks pass. The Function pages stay published from `main` until #4534 hides them, so hold publication until the complete stack is integrated.
71 lines
3.3 KiB
Plaintext
71 lines
3.3 KiB
Plaintext
---
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title: "LanceDB OSS or Enterprise?"
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sidebarTitle: "OSS and Enterprise"
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description: "Start with an embedded library, or use the LanceDB Enterprise multimodal lakehouse for shared AI workloads."
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icon: compass
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keywords: ["oss", "enterprise", "embedded", "deployment", "availability", "comparison"]
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---
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LanceDB gives you two ways to work with multimodal data, both built on the open
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[Lance](/basics/lance) format.
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**LanceDB OSS** is an embedded library. Run it inside your application
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with tables on local disk or in object storage. You control the application,
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its resources, and table maintenance, without a separate database service.
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[Try the quickstart](/quickstart) to create a table and run your first search.
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**LanceDB Enterprise** is a multimodal lakehouse for data curation, feature
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engineering, search, and training data access. It adds query-serving capacity,
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data caching, and background operations for teams working with shared
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multimodal datasets.
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[Connect to Enterprise](/basics/connect#enterprise) when your cluster is ready.
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<span id="labels" />
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<span id="availability" />
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## Why choose Enterprise? {#why-enterprise}
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### Serve growing workloads {#serving}
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Add query-serving capacity as more applications and users depend on your data.
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Enterprise spreads query traffic across a fleet and caches frequently read
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table data near compute, reducing repeated reads from object storage. Query
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serving and background work use separate resources, so you can size each for
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your workload. See [Enterprise architecture](/enterprise/architecture).
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### Reduce operational work {#operations}
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Let the service handle routine table maintenance instead of scheduling it in
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application code. Enterprise handles background [compaction](/maintenance/compaction) and can
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[clean up old table versions](/maintenance/cleanup) according to your retention
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policy. Configure these maintenance tasks for your Enterprise cluster so each
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application does not have to schedule them.
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### Fit your deployment requirements {#deployment}
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Choose a managed deployment or bring LanceDB into your own cloud account.
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Enterprise integrates with OpenTelemetry for metrics and traces, helping your
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team monitor the service alongside your applications. Talk to us about your
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cloud, networking, and operational requirements to plan the right deployment.
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The [Enterprise overview](/enterprise) explains the available options.
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### Connect your data workflows {#workflows}
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Use the same tables for retrieval, dataset preparation, and training data access.
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With its [SQL endpoint](/basics/sql) enabled, Enterprise supports analytical
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[curation](/curation), including joins, grouping, and sampling.
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[Feature engineering](/feature-engineering) adds derived columns and tables;
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computed columns and materialized views require the corresponding features to
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be enabled for your Enterprise cluster.
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[Geneva](/geneva) runs Python feature backfills as distributed jobs.
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[Training data loaders](/training/data-loading), available in both offerings,
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read the resulting datasets for model training.
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## Plan your Enterprise deployment {#get-started}
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[Talk to us about your workload](https://www.lancedb.com/contact) to discuss your
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data, query traffic, pipelines, and deployment requirements.
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For a closer look at how the service runs, read the
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[Enterprise architecture](/enterprise/architecture).
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