Labelled property graph platforms
LPG platforms make graph traversal and application development approachable through labelled nodes, relationships, and languages such as Cypher and GQL. Legra preserves that interface while connecting it to RDF meaning, inference, governed workspaces, provenance, and distributed data logistics.
Where this category excels
Accessible graph models for developers and application teams.
Traversal-oriented querying and strong graph-application ecosystems.
Operational graph workloads, algorithms, and visualization tools.
Where Legra extends the model
Cypher and GQL can benefit from ontology-backed meaning and Datalog-grade inference.
Branches, commits, validation, search, tasks, and provenance share one versioned workspace state.
LPG applications can participate in sovereign multi-party agreements and Data Product exchange.
Questions to use in an evaluation
Will the graph remain an application database, or become shared organizational knowledge?
Do business concepts need portable semantics beyond one database schema?
Must agents and workflows operate on reviewed branches with durable evidence?
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.
Multi-model database with native graph, document, and key/value support
| Feature | Legra | ArangoDB | LadybugDB | GraphQLite |
|---|---|---|---|---|
| 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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