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# Introducing strands-dynamodb-storage: Durable agent storage for the Strands Agents SDK

**[AWS Database Blog](https://daily.dev/sources/aws-database-blog)** · 11 min read · 0 upvotes · 0 comments

## Summary

AWS announces strands-dynamodb-storage, an open source DynamoDB storage backend for the Strands Agents SDK, available on PyPI and npm under Apache 2.0. It implements the SDK's Storage byte contract on a single DynamoDB table, backing session state, transcripts, and long-term memories, and adds S3 offload for large values, gzip compression, TTL, and multi-tenant key prefixes. A DynamoDB vector index on the same table enables semantic memory recall via SearchVectors, eliminating the need for a separate vector database. Requires strands-agents 1.48.0+ or @strands-agents/sdk 1.10.0+, boto3 1.43.64+, and Node.js 20+. The package is v0.1, intended for development and experimentation, with standard DynamoDB and vector index pricing applying plus embedding model costs.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://aws.amazon.com/blogs/database/introducing-strands-dynamodb-storage-durable-agent-storage-for-the-strands-agents-sdk>

## Questions this post answers

### What is strands-dynamodb-storage and what does it do for Strands agents?

It is an open source DynamoDB storage backend for the Strands Agents SDK, available on PyPI and npm under Apache 2.0. It implements the SDK's Storage contract (write, read, delete, list) on a single DynamoDB table, backing session state, transcripts, and long-term memories, and adds S3 offload, gzip compression, TTL, and multi-tenant key prefixes.

_Explore how teams are wiring durable storage into AI agents on daily.dev._

### How can I give a Strands agent semantic memory recall without a separate vector database?

DynamoDB vector indexes let a Strands agent search memories by meaning on the same table that holds its session state, so no separate vector database or data pipeline is needed. Embeddings are generated with Amazon Titan Text Embeddings V2 (1,024 dimensions by default) and searched with the SearchVectors API scoped to a single partition per tenant.

_Track new patterns for agent memory and vector search architectures on daily.dev._

### What are the minimum version requirements to use strands-dynamodb-storage with the Strands Agents SDK?

Python 3.10 or later with strands-agents 1.48.0 and boto3 1.43.64 or later, or Node.js 20 or later with @strands-agents/sdk 1.10.0 and @aws-sdk/client-dynamodb 3.1103.0 or later. These are the versions where the Storage contract and the SearchVectors API respectively became available.

_Keep dependency floors straight when upgrading agent SDKs by following updates on daily.dev._

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---

Tags: [#aws](https://daily.dev/tags/aws), [#ai-agents](https://daily.dev/tags/ai-agents), [#vector-search](https://daily.dev/tags/vector-search), [#aws-dynamodb](https://daily.dev/tags/aws-dynamodb)

[View this post on daily.dev](https://daily.dev/posts/introducing-strands-dynamodb-storage-durable-agent-storage-for-the-strands-agents-sdk-8q1uxxvef)

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