Amazon DocumentDB (with MongoDB compatibility) now offers vector search, a built-in capability that lets you store, index, and search millions of vectors with millisecond response times within your document database for semantic similarity search.

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<p>This article announces the general availability of vector search for Amazon DocumentDB (with MongoDB compatibility). Vector search allows you to store, index, and search millions of vector embeddings within your document database.</p>
<p>Specifically, the article covers:</p>
<ul>
<li>What vector search is and how it can be used for semantic search, product recommendations, and chatbots</li>
<li>How to get started with vector search on Amazon DocumentDB, including generating vector embeddings, inserting them into your database, and creating a vector index</li>
<li>An example of how to search for similar vector embeddings using the new $search aggregation pipeline operator</li>
<li>The availability of vector search at no additional cost for Amazon DocumentDB 5.0 clusters in all AWS regions</li>
</ul>
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Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available

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