vs

AllegroGraph vs Graphwise GraphDB (Ontotext)

AllegroGraph: Lisp-built RDF and document knowledge graph with vector store, reasoning and LLM agents. Graphwise GraphDB (Ontotext): Standards-compliant RDF triplestore with reasoning, connectors and MCP support for GraphRAG.

key differences

  • AllegroGraph is built for larger datasets (≤ 1 PB) than Graphwise GraphDB (Ontotext) (≤ 10 TB).
  • Horizontal scaling is native in AllegroGraph and none in Graphwise GraphDB (Ontotext).
  • Only AllegroGraph has json, stored procedures.
  • Only Graphwise GraphDB (Ontotext) has streaming ingest.

choose allegrograph for

  • +Neuro-symbolic AI and GraphRAG
  • +Healthcare and life-sciences knowledge graphs
  • +Intelligence and event analytics with spatio-temporal reasoning
  • +Entity-event knowledge graphs

best at · Knowledge graph, RAG, Vector search

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

overview
Primary model
RDF / Triple Store
RDF / Triple Store
Also supports
Document, Vector
Graph
Type
Database engine
Database engine
Status
Active
Active
Developer
Franz Inc.
Graphwise
First release
2004
2014
Latest version
9.1.0 (Oct 15, 2026)
11.5.2 (Oct 16, 2026)
License
ProprietaryProprietary (free edition with triple limit)
ProprietaryProprietary (Free and Enterprise editions)
Free tier
✓
✓
popularity
WhichDB Score
16.1
15.6
Rank
#200
#208
GitHub stars
–
–
Stack Overflow questions
79
557
scale & guarantees
Comfortable data size
Large (≤ 1 PB)
Medium (≤ 10 TB)
Horizontal scaling
Native
None
Multi-region
Read replicas
None
ACID
Full
Full
Consistency
Strong
Strong
Schema
Flexible
Flexible
Architecture
Single node, Distributed, Client server
Single node, Primary replica, Client server
deployment
Self-hosted
✓
✓
Vendor-managed cloud
✓
—
Serverless
—
—
Embedded
—
—
Edge
—
—
Clouds
AWS
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, Prolog, Lisp
SPARQL, GraphQL
Client languages
Java, Python, JavaScript, Common Lisp
Java (RDF4J), Python, JavaScript
Best for
Knowledge graph, RAG, Vector search, Geo
Knowledge graph, RAG, Metadata, Content

AllegroGraph vs Graphwise GraphDB (Ontotext): FAQ

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

AllegroGraph: Lisp-built RDF and document knowledge graph with vector store, reasoning and LLM agents. Graphwise GraphDB (Ontotext): Standards-compliant RDF triplestore with reasoning, connectors and MCP support for GraphRAG. AllegroGraph is built for larger datasets (≤ 1 PB) than Graphwise GraphDB (Ontotext) (≤ 10 TB). Horizontal scaling is native in AllegroGraph and none in Graphwise GraphDB (Ontotext). Only AllegroGraph has json, stored procedures.

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

Choose AllegroGraph for neuro-symbolic AI and GraphRAG; healthcare and life-sciences knowledge graphs; and intelligence and event analytics with spatio-temporal reasoning. Choose Graphwise GraphDB (Ontotext) for enterprise knowledge graphs; publishing and media content metadata; and life-sciences data integration.

Is AllegroGraph or Graphwise GraphDB (Ontotext) more popular?

AllegroGraph ranks #200 on the WhichDB Score (16.1/100) and Graphwise GraphDB (Ontotext) ranks #208 (15.6/100). Popularity is not fit: check the requirements that matter for your project.

Are AllegroGraph and Graphwise GraphDB (Ontotext) open source?

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