Developers
In memory
knowledge graph
A graph is only useful if walking it is cheap. Held in memory and typed, traversal becomes something you can put behind a search box rather than behind a nightly job.
Capabilities
Connect data and use it across applications and AI
The schema the graph enforces is the schema your code sees and the schema the model is handed.
Types you define
Model the entities your domain actually has, rather than bending everything into documents.
Traversal at speed
Multi-hop queries in memory, fast enough to sit inside an interactive request.
Revisions kept
History is part of the model, because in industrial data the previous version is often the question.
Records stay put
The graph references the source system rather than copying it into a second store to drift.
Permissions on edges
Relationship-based access, so what you can reach depends on how you reached it.
Incremental updates
Changes land continuously instead of waiting for a rebuild window.
Questions for developers
The things worth asking first
Is this a triple store?
No. It is a typed property graph stored in RocksDB, with nodes and their edges kept in memory for traversal, and full text and vector indexes in the same process. There is no RDF or SPARQL layer.
Does it replace my database?
No. Studio keeps a synced copy of the records it needs and links back to each source. Your systems keep their role, their validation and their audit trail.
How large can it get?
Deployments run over 30TB of connected data in production.
Your data. Your infrastructure.