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title: 'Vector Engines' sidebar_label: 'Vector Engines' description: 'Configure vector engines for efficient embedding storage and similarity search in Spice.' sidebar_position: 7 pagination_prev: null pagination_next: null

🎓 Learn how it works with the Amazon S3 Vectors with Spice engineering blog post.

Data sourced by Data Connectors, or views built atop them with vector embedding columns can be indexed and efficiently searched using a vector engine.

A vector engine will store all vector embeddings associated with columns in a dataset/view, provide efficient vector search operations and avoid unnecessary recomputation of embeddings.

A vector engine is configured by setting the vectors configuration. E.g.

For the complete reference specification see datasets.

Supported Vector engines:

Name	Description
s3_vectors	AWS S3 vectors

:::warning[Limitations]

• A dataset or view must be accelerated (i.e. datasets[].acceleration.enabled: true, see docs) for a vector engine to be provided the appropriate data to ingest.

  :::

Vector Engine Docs

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