Concepts

The ideas that make RelataDB different from a regular database. Each page below covers why a capability exists, the model behind it, and how it shows up in queries — without reproducing the full API reference.

In this section

  • AI in RelataDB — the agent-native surface: memory, governed tools, and multi-agent coordination
  • Ontology & Schema — declare types, not tables; how ObjectType / EventType / LinkType drive storage and the planner
  • Bi-Temporal — every row carries valid and system time; rewind the database with AS OF
  • Identity — deterministic canonical-identifier resolution; how the graph forms itself
  • Governance — cell-level ACL and PURPOSE compiled into the scan predicate
  • Provenance — tamper-evident, hash-chained lineage on every fact
  • Agent Memory — the cognitive-memory model: remember · recall · justify · consolidate · forget
  • Hybrid Search — BM25 + HNSW vector + identity fusion, ranked in one query
  • Federation — the roadmap for federated queries across RelataDB instances
  • Relata vs Others — where RelataDB fits against Postgres, Neo4j, Pinecone, and agent-memory tools (and when not to use it)

See also: Architecture for how these concepts are implemented, and the Reference for the exact verbs, arguments, and response shapes.