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Vector Search Limitations
Learn the limitations of the TiDB vector search.

Vector Search Limitations

This document describes the known limitations of TiDB vector search.

Warning:

The vector search feature is experimental. It is not recommended that you use it in the production environment. This feature might be changed without prior notice. If you find a bug, you can report an issue on GitHub.

Note:

The vector search feature is only available for TiDB Self-Managed clusters and TiDB Cloud Serverless clusters.

Vector data type limitations

  • Each vector supports up to 16383 dimensions.
  • Vector data types cannot store NaN, Infinity, or -Infinity values.
  • Vector data types cannot store double-precision floating-point numbers. If you insert or store double-precision floating-point numbers in vector columns, TiDB converts them to single-precision floating-point numbers.
  • Vector columns cannot be used as primary keys or as part of a primary key.
  • Vector columns cannot be used as unique indexes or as part of a unique index.
  • Vector columns cannot be used as partition keys or as part of a partition key.
  • Currently, TiDB does not support modifying a vector column to other data types (such as JSON and VARCHAR).

Vector index limitations

See Vector search restrictions.

Compatibility with TiDB tools

  • Make sure that you are using v8.4.0 or a later version of BR to back up and restore data. Restoring tables with vector data types to TiDB clusters earlier than v8.4.0 is not supported.
  • TiDB Data Migration (DM) does not support migrating or replicating MySQL 9.0 vector data types to TiDB.
  • When TiCDC replicates vector data to a downstream that does not support vector data types, it will change the vector data types to another type. For more information, see Compatibility with vector data types.
  • The Data Migration feature in the TiDB Cloud console does not support migrating or replicating MySQL 9.0 vector data types to TiDB Cloud.

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