GibRAM
Graph in-Buffer Retrieval & Associative Memory
Graph in-Buffer : Graph structure (entities + relationships) stored in RAM
: Graph structure (entities + relationships) stored in RAM Retrieval : Query mechanism for retrieving relevant context in RAG workflows
: Query mechanism for retrieving relevant context in RAG workflows Associative Memory: Traverse between associated nodes via relationships, all accessed from memory
GibRAM is an in-memory knowledge graph server designed for retrieval augmented generation (RAG) workflows. It combines a lightweight graph store with vector search so that related pieces of information remain connected in memory. This makes it easier to retrieve related regulations, articles or other text when a query mentions specific subjects.
Why GibRAM?
In memory and Ephemeral: Data lives in RAM with a configurable time to live. It is meant for short lived analysis and exploration rather than persistent storage.
Graph and Vectors Together: Stores named entities, relationships and document chunks alongside their embeddings in the same structure.
Graph aware Retrieval: Supports traversal over entities and relations as well as semantic search, helping you pull in context that would be missed by vector similarity alone.
... continue reading