Valkey Document Store

[daric93]

Summary and motivation

ValkeyDocumentStore will provide Haystack users with a high-performance, open-source alternative for vector search and metadata filtering. Valkey is a Redis-compatible in-memory database that supports persistence, making it ideal for both prototyping and production environments.

Detailed design

Introduce ValkeyDocumentStore as a built-in integration for Haystack. This component will implement Haystack’s DocumentStore interface using Valkey’s search module for vector similarity and metadata-based filtering.

Valkey supports all essential capabilities required by the DocumentStore interface.

Checklist

If the request is accepted, ensure the following checklist is complete before closing this issue.

Tasks

• The code is documented with docstrings and was merged in the main branch
• Docs are published at https://docs.haystack.deepset.ai/
• There is a Github workflow running the tests for the integration nightly and at every PR
• A new label named like integration:<your integration name> has been added to the list of labels for this repository
• The labeler.yml file has been updated
• The package has been released on PyPI
• An integration tile with a usage example has been added to https://github.com/deepset-ai/haystack-integrations
• The integration has been listed in the Inventory section of this repo README
• The feature was announced through social media

[daric93]

If this integration aligns with Haystack’s roadmap, I’d be happy to implement this.

[daric93]

While waiting for feedback, I’ve started working on the ValkeyDocumentStore implementation to explore feasibility and ensure alignment with Haystack’s interface.