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# Agent Memory Head to Head

**[Medium](https://daily.dev/sources/medium_js)** · 8 min read · 0 upvotes · 0 comments

## Summary

A hands-on comparison of two approaches to giving AI agents long-term memory: a hand-rolled always-on sample from Google's generative-ai repo (built with Google ADK and Gemini 3.1 Flash Lite) versus the managed Vertex AI Memory Bank service. Both were tested on identical inputs — a markdown file, a chat screenshot, and an audio memo. The self-hosted sample uses SQLite with a recent-window retrieval (LIMIT 50, no vector search), multi-agent orchestration adding 2.4–4.7s per ingest, and has no per-user isolation or governance. Vertex AI Memory Bank deduplicates and merges memories, scopes by user_id, and returns similarity-ranked results in 0.7s. The recommendation: use the sample to learn the mechanics, switch to managed Memory Bank for production use cases requiring scale, isolation, and real retrieval.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://medium.com/google-cloud/agent-memory-head-to-head-469fd1cb71a0>

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---

Tags: [#ai-agents](https://daily.dev/tags/ai-agents), [#google-gemini](https://daily.dev/tags/google-gemini), [#vertex-ai](https://daily.dev/tags/vertex-ai)

[View this post on daily.dev](https://daily.dev/posts/agent-memory-head-to-head-1ovyjwqy2)

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