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Ask HN: What's your experience with using graph databases for agentic use-cases?

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Re: Ask HN: What's your experience with using graph databases for agentic use-cases?

#52
I am glad I stumbled upon this thread. I’ve not heard positive things in the past about graph dbs. That said, working with legal documents, it makes sense to have both vector and graph search (after candidate refinement) for this domain…

Re: Ask HN: What's your experience with using graph databases for agentic use-cases?

#53

Neo4j has a GraphRAG book that I've found very helpful: https://neo4j.com/essential-graphrag/ It depends on the shape of your data. In my domain (cloud security), there are many many entities and it's very valuable to map out how they relate to each other. For example, we often want to answer a question like: “Which publicly exposed EC2 instances are used by IAM roles that have administrative privileges in my AWS acc…

I've recently started playing with graphDBs mostly for the purpose of using entities within parsed documents for my own ideas on a modified RAG approach (not graphRAG). However I'm not sure I would choose this for serious production type work compared to object stores like Mongo where your entity could easily have additional metadata sections of information in it's object store which could have anything you want. Right now as I brainstorm, I find that the graphDB just fits better with my mental thought meanderings.

Re: Ask HN: What's your experience with using graph databases for agentic use-cases?

#54
It boils down to whether your LLMs can speak graph queries better than SQL, for your use cases and data. As your data posture changes and your use cases change, you routinely reevaluate which DB query language suits best for LLMs.

I'd also design the system architecture in such a way that your non-agentic workloads don't suffer if you have to move between query models for serving agentic workloads better.

Re: Ask HN: What's your experience with using graph databases for agentic use-cases?

#56
We are using neo4j to power our agents at QA.tech.

Essentially to make it behave more like a human so that it learns and builds up an understanding of the pages it should test we map interactions into a knowledge graph stored in Neo4j. The consists of Pages and Actions on the page as well as links to documentation sections and other relevant info, together with descriptions, metadata and embeddings for search.

To make the agents better at planning and understanding the context of the page it can search the graph for relevant information and expand through the graph for more context.

This works remarkably well. I think our agents (when they have interacted a bit w the page) are some of the best browser agents I have tested.

I would highly recommend this but you need to put some effort into a nice ontology for the graph and making the tolling right for your use case. Its really not just plug and play. :)

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