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Graphwise GraphDB (Ontotext) vs Stardog

Graphwise GraphDB (Ontotext): Standards-compliant RDF triplestore with reasoning, connectors and MCP support for GraphRAG. Stardog: Enterprise knowledge-graph platform: RDF store, reasoning and virtual graphs over your sources.

key differences

  • Only Graphwise GraphDB (Ontotext) has vector search, encryption at rest, streaming ingest.

choose ontotext-graphdb for

  • +Enterprise knowledge graphs
  • +Publishing and media content metadata
  • +Life-sciences data integration
  • +Taxonomy and ontology-backed search

best at · Knowledge graph, RAG, Metadata

choose stardog for

  • +Enterprise data fabric and semantic layer
  • +Life-sciences and pharma knowledge graphs
  • +Regulatory and compliance data integration
  • +Natural-language question answering over enterprise data

best at · Knowledge graph, Metadata, RAG

Graphwise GraphDB (Ontotext)Standards-compliant RDF triplestore with reasoning, connectors and MCP support for GraphRAG.
StardogEnterprise knowledge-graph platform: RDF store, reasoning and virtual graphs over your sources.
overview
Primary model
RDF / Triple Store
RDF / Triple Store
Also supports
Graph
Graph
Type
Database engine
Database engine
Status
Active
Active
Developer
Graphwise
Stardog Union
First release
2014
2012
Latest version
11.5.2 (Oct 16, 2026)
12.2.1 (Oct 26, 2026)
License
ProprietaryProprietary (Free and Enterprise editions)
ProprietaryProprietary (free 1-year renewable license available)
Free tier
✓
✓
popularity
WhichDB Score
15.6
12.7
Rank
#208
#265
GitHub stars
–
–
Stack Overflow questions
557
97
scale & guarantees
Comfortable data size
Medium (≤ 10 TB)
Medium (≤ 10 TB)
Horizontal scaling
None
None
Multi-region
None
None
ACID
Full
Full
Consistency
Strong
Strong
Schema
Flexible
Flexible
Architecture
Single node, Primary replica, Client server
Single node, Primary replica, Client server
deployment
Self-hosted
✓
✓
Vendor-managed cloud
—
✓
Serverless
—
—
Embedded
—
—
Edge
—
—
Clouds
AWS, Azure
AWS, Azure
capabilities
Transactions
✓
✓
Joins
—
—
Secondary indexes
—
—
Full-text search
✓
✓
Vector search
✓
—
Geospatial
✓
✓
JSON
—
—
Change data capture
—
—
Triggers
—
—
Stored procedures
—
—
Materialized views
—
—
TTL / expiry
—
—
Pub/Sub
—
—
Columnar storage
—
—
In-memory
—
—
Durable persistence
✓
✓
Compression
—
—
Encryption at rest
✓
—
Role-based access
✓
✓
Time travel
—
—
Branching
—
—
Online schema changes
✓
✓
Streaming ingest
✓
—
Offline sync
—
—
Runs in WebAssembly
—
—
interfaces
Query languages
SPARQL, GraphQL
SPARQL, GraphQL, SQL, Stardog Rules
Client languages
Java (RDF4J), Python, JavaScript
Java, Python, JavaScript, .NET
Best for
Knowledge graph, RAG, Metadata, Content
Knowledge graph, Metadata, RAG, Traversal
Add more to this comparisonNot sure either fits? Try smart match

Graphwise GraphDB (Ontotext) vs Stardog: FAQ

What is the difference between Graphwise GraphDB (Ontotext) and Stardog?

Graphwise GraphDB (Ontotext): Standards-compliant RDF triplestore with reasoning, connectors and MCP support for GraphRAG. Stardog: Enterprise knowledge-graph platform: RDF store, reasoning and virtual graphs over your sources. Only Graphwise GraphDB (Ontotext) has vector search, encryption at rest, streaming ingest.

When should I choose Graphwise GraphDB (Ontotext) over Stardog?

Choose Graphwise GraphDB (Ontotext) for enterprise knowledge graphs; publishing and media content metadata; and life-sciences data integration. Choose Stardog for enterprise data fabric and semantic layer; life-sciences and pharma knowledge graphs; and regulatory and compliance data integration.

Is Graphwise GraphDB (Ontotext) or Stardog more popular?

Graphwise GraphDB (Ontotext) ranks #208 on the WhichDB Score (15.6/100) and Stardog ranks #265 (12.7/100). Popularity is not fit: check the requirements that matter for your project.

Are Graphwise GraphDB (Ontotext) and Stardog open source?

No. Graphwise GraphDB (Ontotext) is proprietary, closed-source software. No. Stardog is proprietary, closed-source software.