RDF and semantic graph platforms

RDF is part of the foundation, not the boundary of the product.

RDF platforms provide standards-based representation, SPARQL querying, ontologies, reasoning, and semantic integration. Legra uses that foundation while treating the workspace, governed work, distribution, evidence, agreements, and economic exchange as equally fundamental parts of the system.

Where this category excels

Standards-based graph representation and global identifiers.

SPARQL querying, ontology-backed meaning, and rule-based inference.

Mature tooling for semantic integration, governance, and knowledge graphs.

Where Legra extends the model

RDF and LPG interfaces participate in one branch-sensitive graph infrastructure.

Sovereign workspaces combine graph data with files, history, tasks, conversations, rights, and evidence.

Data logistics spans governed change, custody, replication, execution, contracts, and settlement rather than database access alone.

Questions to use in an evaluation

Do you need only a semantic database, or a corpus in which work and knowledge improve together?

Must multiple parties retain independent authority over private and shared graph data?

Do Use Cases need to connect graph meaning to execution, review, evidence, and value flows?

Beyond database features

Graph features are only the substrate.

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.

A complete history of the work

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.

Work by people, AI agents, and automated services appears in one traceable record.
See what is happening now, then return to the same history later for review.

Explore activity history

Layered provenance

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.

Evidence answers who or what acted, on whose authority, from which inputs, and with which result.
Commit, activity, fact-origin, and derivation evidence remains attached to the workspace and its history.

Reasoning and derivations

Composable transaction pricing

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.

Charges, credits, refunds, penalties, and commissions contribute to the final amount.
Zero is an explicit price through the same accounting path, including self-operated work.

Data logistics infrastructure

Multidirectional token settlement

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.

Tokens can flow to data owners, infrastructure and service Operators, and the NetworkOperator treasury.
The same evidence supports internal chargeback and external settlement; subscriptions supply token packages rather than feature gates.

Data Products and contracts

Product-level technical deep dive

RDF and semantic graph platforms: product matrix.

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.

Legra

Sovereign, content-addressed graph data logistics infrastructure

RustProprietary

Stardog

Enterprise knowledge graph platform with data virtualization

JavaProprietary

GraphDB

Semantic repository with reasoning and high-availability clustering

JavaProprietary + Free Edition

Amazon Neptune

Fully managed AWS graph database for RDF and property graphs

Not disclosedProprietary

AllegroGraph

Federated triplestore with neuro-symbolic AI and vector store

LispProprietary + Free Edition

RDFox

High-performance in-memory RDF triplestore with Datalog reasoning

C++Proprietary

Virtuoso

Universal server with SQL/SPARQL hybrid and data virtualization

CProprietary + Open Source Edition

Feature	Legra	Stardog	GraphDB	Amazon Neptune	AllegroGraph	RDFox	Virtuoso
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

Continue exploring

Follow the connected topics.

Choose your perspective

Compare RDF and SPARQL engines Compare LPG platforms Query-language documentation Reasoning documentation Knowledge graph infrastructure