Introducing HonuDB

Why does the world need yet another database? In short, because no one database can support all use cases all the time. HonuDB is for machine learning engineers, a group that needs data management more than most, but is often overlooked as users for database management systems.

Instead of creating a single purpose tool like a vector database, or augmenting an existing database with vector capabilities like Elastic; HonuDB is focused on the workflow of AI and model development from training datasets to inferencing context.

The AI/ML workflow has specialized features that are not generally found together in a single system. To support reproducibility, datasets must be versioned and snapshotted so that training datasets can be mapped to their models, and datasets are a first class access pattern in HonuDB. We also understand how important privacy and data governance is, especially when it comes to AI – so HonuDB is built to support provenance based investigations and geographic access controls. ML datasets range from the very small to the very large, so HonuDB can operate as a single node or scale to replicate to hundreds of nodes across multiple geographic regions. Finally, vector queries and model context protocols are needed for inferencing, and Honu is ready to support these protocols for RAG workflows.

HonuDB not only supports AI/ML workflows but uses ML under the hood to improve its performance. Based on the academic papers Anti-Entropy Bandits for Geo-Replicated Consistency and Bilateral Anti-Entropy for Eventual Consitency, HonuDB uses reinforcement learning to optimize replication and consistency in the wide area!

Always open-source, we hope HonuDB will accelerate your projects and that you’ll enjoy using it as much as we do.