Stardog
RDF-native semantic platform with SHACL validation, virtual graphs, and the Voicebox AI assistant. $32.5M funding. Pitches itself as a governed-knowledge layer.
At a glance
- Type
- RDF semantic platform + Voicebox AI
- Tier
- T1
- Section
- Knowledge-graph platforms
- Created
- 2010
- Latest release
- not applicable — not OSS
- License
- not applicable — not OSS
- GitHub
- not applicable — no GitHub repo
- Pricing
- Enterprise only
- Funding
- $32M Series C (last known) · 2022-01
Taxonomy
- storage
- graph
- retrieval
- graph-traversal
- persistence
- long-term
- update
- overwrite
- unit
- fact
- governance
- auditable
- conflict
- overwrite
When to use
Optimised for: relationship modeling + reasoning + governance over pure vector
Anti-fit: not for purely-vector or simple-RAG use cases (graph adds setup cost)
Pros & cons
Pros
Mature semantic graph + virtualization (data fabric over relational/cloud sources); strong inference rules engine.
Cons
Enterprise-tier pricing and complexity; smaller community than Neo4j; license shifted to Stardog Studio commercial focus.
Claims & capabilities
$32.5M total funding (Series C; 2022); customers include Boehringer Ingelheim, Schneider Electric, NASA, U.S. Department of Defense; Voicebox AI launched 2024 — early access "to dozens of existing customers and new prospects" in manufacturing/pharma; Helix Finance case study reports 40% reduction in regulatory review cycles. Accenture Ventures strategic investment 2025
Technical surface
- API surface
- REST, SPARQL, SDK: Java, Python, JS
- Backend storage
- custom (RDF triple store)
- Deployment
- Both
- Embedding model
- BYO
- Multi-tenancy
- Per-database access control; on-prem / private-cloud / SaaS options
- MCP
- no first-party MCP adapter published as of 2026-05; community connectors may exist.
- A2A
- no Google A2A (Agent2Agent) integration documented as of 2026-05.
- OpenTelemetry
- first-class — Prometheus + OTel
Similar systems
Other knowledge-graph platforms in the catalog, ranked by inbound references.
- Neo4j T1
Property graph DB with Cypher; native vector search; Aura Agent + MCP server for graph-as-memory. $100M GenAI investment in 2025.
- Amazon Neptune Analytics T1
Vector index on graph nodes queryable via openCypher. Mem0 integration GA 2025; Cognee integration for agentic RAG. Combines semantic recall with multi-hop traversal in one managed service.
- AllegroGraph (Franz) T1
RDF triple/quad store with RDFS++ / OWL reasoning. v8.4 (May 2025) added an NLQ interface.
- Apache AGE T2
openCypher over Postgres. Pairs with pgvector for graph + vector hybrid retrieval. Azure Database for PostgreSQL ships AGE with ai_extension LLM functions for entity extraction directly in SQL.
- ArangoDB T1
HybridGraphRAG combines vector search, graph traversal, full-text in one AQL query. ArangoGraphML for ML pipelines; LangChain integration.
- Dgraph T2
Vector indexing on any node. Google Gen AI Toolbox integration; LangChain agent orchestration.