Amazon DocumentDB now supports vector search, a capability that allows storing, indexing, and searching millions of vectors for machine learning and generative AI applications with millisecond response times, eliminating the need for separate vector infrastructure and data duplication.

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<p>The article announces the launch of vector search for Amazon DocumentDB, a new capability that enables storing, indexing, and searching millions of vectors with millisecond response times, enabling semantic search and other AI applications.</p>
<p>Specifically, the article covers:</p>
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<li>Vector search for Amazon DocumentDB can store vectors from Amazon Bedrock, Amazon SageMaker, and more.</li>
<li>Enables searching the database based on meaning, unlocking use cases like semantic search, recommendations, personalization, and chatbots.</li>
<li>No upfront commitments or additional costs, pay only for data stored and compute used.</li>
<li>Available on DocumentDB 5.0 instance-based clusters in all regions where Amazon DocumentDB is available.</li>
<li>Can get started via the AWS Console or AWS CLI, more details on the features page and developer guide.</li>
</ul>
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AWS announces vector search for Amazon DocumentDB

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