mirror of
https://github.com/lancedb/lancedb.git
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Jack Ye
ddb318567a
## Summary - Complete the SQL reference: `ATTACH DATABASE`, the `CHANGES` clause, and `dedupe()`/`duplicate_pairs()` (verified against current sophon source; these were recently renamed from `vector_dedup`/`vector_duplicate_pairs`). Fix the blob-column default-projection claim and add the previously undocumented `blob_descriptor()`. - Enrich the gated Functions draft (still `.mintignore`'d, pre-release): chained Functions over blob outputs, GPU-produced blobs, Secrets, multi-input/output binding, `code=[module]` packaging. - Upgrade the materialized-view and computed-column auto-refresh drafts with precise, verified catch-up semantics, and add the missing `ALTER MATERIALIZED VIEW` / `CREATE ... WITH(...)` sections (also gated — the automatic-refresh scheduler is still dev/staging-only). - Thread one running example (video frames → GPU extract/caption → dedup → auto-refreshing materialized view) through Functions, materialized views, and the LeRobotDataset integration guide instead of a separate tutorial. - Rename "LanceDB OSS"/"OSS" to "LanceDB Embedded"/"Embedded" throughout (52 files); activate the existing availability-comparison mechanism on `basics/offerings.mdx` for a full feature-by-feature comparison table.
46 lines
1.8 KiB
Plaintext
46 lines
1.8 KiB
Plaintext
---
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title: "Lance format"
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sidebarTitle: "Lance Format"
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description: "The open format for multimodal data behind LanceDB."
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icon: "/static/assets/logo/lance-logo-gray.png"
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keywords: ["lance", "format", "multimodal", "versioning", "column evolution"]
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---
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## Lance format overview {#standard}
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[Lance](https://lance.org/) is an open-source, columnar format designed for
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multimodal AI. It defines how data is stored and organized into versioned tables.
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<span id="embedded" />
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<span id="enterprise" />
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LanceDB Embedded and LanceDB Enterprise both use Lance as their storage foundation.
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The format is developed as an independent open-source project, with its own
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specification and tools.
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## Multimodal data {#storage}
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A Lance table can hold images, video, audio, text, embeddings and structured
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metadata together. For example, a video dataset can keep each clip alongside
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its caption, labels and embeddings, so applications can search and work with
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those fields together.
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## Data access, versioning and column updates {#capabilities}
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- **Efficient data access.** Read individual rows for retrieval and training,
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or scan columns for analytics.
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- **Versioned data.** Read an earlier table version to reproduce an experiment
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or inspect previous results, while that version is retained.
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- **Independent column updates.** Add embeddings or other derived features
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without rewriting the existing image, video or text columns.
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## Learn more {#next}
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<span id="versioning" />
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<span id="evolution" />
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- [Lance format specification](https://lance.org/format): how the format works.
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- [Table versioning](/management/table#versioning): read and manage table versions.
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- [Computed columns](/feature-engineering/add-computed-column): add derived features to your data.
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- [Architecture](/#architecture): how LanceDB Embedded and Enterprise build on Lance.
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