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Fluree DB

A semantic graph database with time travel, branching, and verifiable data — built on W3C standards.

Fluree DB is a single binary that stores your data as an RDF knowledge graph, queryable with SPARQL or JSON-LD Query, with every commit immutably recorded so you can travel back to any prior state. It supports git-style branching and merging, signed and policy-gated transactions, SHACL validation, OWL/RDFS reasoning, and full-text and vector search — over local files, S3, or IPFS — without bolting on external services.

What you get

  • Semantic by default. Your data is RDF. IRIs, JSON-LD @context, named graphs, and typed values are first-class. Queries are SPARQL 1.1 or the equivalent JSON-LD Query, both compiling to the same execution engine.
  • Property graphs and statement-level metadata. Attach properties to a relationship, not just a node — role and since on a worksFor edge, source and confidence on a claim — with RDF 1.2 / SPARQL 1.2 edge annotations. Labeled-property-graph edges, parallel relationships between the same two nodes, and RDF-star provenance all live on one surface, and plain triple queries are left undisturbed. See Edge annotations.
  • Time travel. Every transaction is a commit on an immutable chain. Query the state of the graph at any past moment with a single t parameter — no snapshots to restore, no separate audit log to consult.
  • Branching and merging. Create a branch off any commit, transact against it in isolation, then merge it back. Useful for staging changes, running what-if analyses, or maintaining environment-specific overlays.
  • Verifiable data. Transactions and commits can be signed (JWS / W3C Verifiable Credentials). The commit chain is content-addressed, so any tampering is detectable. Pair it with policy enforcement to prove who changed what and when they were allowed to.
  • Policy-based access control. Policies are written as graph data, evaluated per query and per transaction, and travel with the ledger — not bolted on at the API layer.
  • Storage your way. Local filesystem for development, S3 + DynamoDB for production, IPFS for content-addressed distribution. The same ledger format works across all of them.
  • Search built in. BM25 full-text indexing and HNSW vector search live alongside SPARQL — no separate search service to operate.
  • Reasoning. OWL/RDFS inference and Datalog rules run inside the query engine, so derived facts are queryable without a materialization step.
  • Embeddable. The same engine that powers the server runs as a Rust library, generic over storage and nameservice. Use it directly in your application or run it standalone over HTTP.

Start here

Explore the docs

  • Concepts — ledgers, graph sources, IRIs, datatypes, edge annotations, time travel, policy, verifiable data, reasoning
  • Guides (cookbooks) — query patterns, search, time travel, branching, policies, SHACL, edge annotations — task-oriented recipes
  • CLI reference — every fluree command, flag by flag
  • HTTP API — endpoints, headers, signed requests, error model
  • Query — JSON-LD Query, SPARQL, output formats, CONSTRUCT, explain plans, reasoning
  • Transactions — insert, upsert, update, conditional updates, signed transactions
  • Security and policy — authentication, encryption, commit signing, policy model
  • Indexing and search — background indexing, BM25, vector search, geospatial
  • Graph sources and integrations — Iceberg/Parquet, R2RML, BM25 graph source
  • Operations — configuration, Docker, storage modes, telemetry, archive/restore
  • Design — internals: query execution, storage traits, index format, nameservice
  • Reference — glossary, vocabulary, OWL/RDFS support, crate map
  • Troubleshooting — common errors, debugging queries, performance tracing
  • Contributing — dev setup, tests, SPARQL compliance, releasing

The full table of contents is in the sidebar.

Building with AI and agents

Fluree for AI and agents features for the AI use case — it ties together Agent JSON (token-efficient query output), the MCP server (Fluree as an agent tool), Fluree Memory, vector and full-text search as a RAG substrate, and reasoning.

Fluree Memory

Fluree Memory is persistent, searchable memory for AI coding assistants — built on Fluree DB and shipped in the same fluree binary. If you’re here for the memory tooling, jump straight to the Memory docs.