Versioned graph databases
Fluree and TerminusDB make immutable history or git-style data versioning central to their graph model. They belong together as versioned graph databases, not in the same product matrix as conventional RDF stores or focused SPARQL engines.
Where this category excels
Immutable or append-oriented history with explicit change over time.
Branching, revision, audit, or time-travel concepts closer to software repositories.
A stronger collaboration model than mutable latest-state-only databases.
Where Legra extends the model
Versioned graph state lives inside sovereign workspaces with files, conversations, tasks, authority, and agreements.
Task trees and activity journals capture how humans, agents, and services produced each valuable change.
Custody, replication, pricing, licensing, and settlement extend the commit model into cross-party data logistics.
Questions to use in an evaluation
Is data history the end goal, or evidence within an ongoing corpus of work?
Must branches connect to authority, review, execution, and commercial agreements?
Can independently operated nodes exchange governed knowledge without one platform owner?
Beyond database features
Legra also organizes the work that uses and changes the graph, the evidence needed to review that work, and the economic relationships that move data and value between parties. That operational layer is what turns graph infrastructure into data logistics infrastructure.
Legra keeps each piece of work together with the changes it made, the evidence behind it, and any costs incurred. That history stays private to the workspace and cannot be quietly rewritten.
Full provenance connects signed commits and exact deltas to task and transaction lineage, actors, delegated authority, imports, and every retained rule and premise behind derived facts.
The admitted total composes independently priced data value, compute, storage, custody, transport, external I/O, rights, and operator services instead of treating bytes as the value of data.
Every resource-consuming operation follows one path: measure, price, authorize, execute, record, and settle. Detailed evidence stays with the workspace instead of one central billing ledger.
Product-level technical deep dive
This matrix includes only products in the same directly comparable family. Adjacent product types belong in their own guide instead of making one oversized, apples-and-oranges scorecard.
| Feature | Legra | Fluree | TerminusDB |
|---|---|---|---|
| Architecture | |||
| Peer-to-peer distribution | |||
| No central server required | |||
| Data Model & Query | |||
| RDF / Linked Data native | |||
| Full-text search | |||
| Query Languages | |||
| RDF 1.2 | |||
| SPARQL 1.1 | |||
| SPARQL 1.2 | |||
| RDF-star (RDF*) | |||
| openCypher | |||
| ISO GQL | |||
| SQL | |||
| Graph Store Protocol | |||
| GraphQL | |||
| Proprietary query language | |||
| Versioning & Branching | |||
| Git-style branching | |||
| Immutable commits | |||
| Delta / diff queries | |||
| Security & Encryption | |||
| Decentralized identity (DIDs) | |||
| planned | |||
| Enterprise & Operations | |||
| High-availability clustering | |||
| OWL / RDFS reasoning engine | |||
| Datalog reasoning | |||
| SWRL / RIF rules | |||
| LPG reasoning | |||
| SHACL / ShEx validation | |||
| Managed cloud offering | |||
| Visual graph explorer / GUI tools | |||
| Production-ready today | |||
| AI & Vector | |||
| Built-in vector search | |||
| Versioned vector indexes | |||
| Encrypted vector search | |||
| Data Model Breadth | |||
| Property graph / LPG support | |||
| ACID transactions | |||
| Immutable transaction history | |||
| Indexing & Performance | |||
| Ad-hoc index creation | |||
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