ArangoDB vs Stardog
ArangoDB vs Stardog: side-by-side comparison of two knowledge-graph platforms systems — architecture, taxonomy, license, pricing, MCP/A2A support, and direct edges.
Cost & capability
| ArangoDB | Stardog | |
|---|---|---|
| Cost tier | mid | — |
Where they differ (9)
Rows where both sides have data and the values disagree — the shortlist of dimensions that actually distinguish these two systems.
| ArangoDB | Stardog | |
|---|---|---|
| Type | Multi-model: graph + doc + KV + vector | RDF semantic platform + Voicebox AI |
| Created | 2014 | 2010 |
| Pricing | Pay-per-use | Stardog Free (renewable 1-year license, commercial use allowed, no HA/caching/backups); Enterprise on-prem and cloud quote-based |
| Funding | Series B · 2021-10 | $32M Series C (last known) · 2022-01 |
| Backend storage | custom (RocksDB-backed multi-model) | custom (RDF triple store) |
| API surface | REST (HTTP), SDK: many | REST, SPARQL, SDK: Java, Python, JS |
| Multi-tenancy | hard-isolation | Per-database access control; on-prem / private-cloud / SaaS options |
| MCP | yes — community ravenwits/mcp-server-arangodb | yes — official Stardog Cloud MCP server (stardog-union/stardog-cloud-mcp; remote setup in beta) |
| OpenTelemetry | first-class | first-class — Prometheus + OTel |
At a glance
| ArangoDB | Stardog | |
|---|---|---|
| Section | Knowledge-graph platforms | Knowledge-graph platforms |
| Tier | T1 | T1 |
| Type | Multi-model: graph + doc + KV + vector | RDF semantic platform + Voicebox AI |
| Created | 2014 | 2010 |
| License | BSL-1.1 (source-available; each release converts to Apache-2.0 four years after release) | — |
| GitHub | arangodb/arangodb — ~14.3k stars, active (commit date not captured) | — |
| Pricing | Pay-per-use | Stardog Free (renewable 1-year license, commercial use allowed, no HA/caching/backups); Enterprise on-prem and cloud quote-based |
| Funding | Series B · 2021-10 | $32M Series C (last known) · 2022-01 |
| Backend storage | custom (RocksDB-backed multi-model) | custom (RDF triple store) |
| Deployment | Both | Both |
| API surface | REST (HTTP), SDK: many | REST, SPARQL, SDK: Java, Python, JS |
| Embedding | BYO | BYO |
| Multi-tenancy | hard-isolation | Per-database access control; on-prem / private-cloud / SaaS options |
| MCP | yes — community ravenwits/mcp-server-arangodb | yes — official Stardog Cloud MCP server (stardog-union/stardog-cloud-mcp; remote setup in beta) |
| A2A | no Google A2A (Agent2Agent) integration documented as of 2026-05. | no Google A2A (Agent2Agent) integration documented as of 2026-05. |
| OpenTelemetry | first-class | first-class — Prometheus + OTel |
| Optimised for | relationship modeling + reasoning + governance over pure vector | relationship modeling + reasoning + governance over pure vector |
| Anti-fit | not for purely-vector or simple-RAG use cases (graph adds setup cost) | not for purely-vector or simple-RAG use cases (graph adds setup cost) |
Pros & cons
ArangoDB
Pros: Multi-model (graph + document + KV) in one engine — useful when memory crosses paradigms without managing multiple databases.
Cons: Multi-model adds complexity vs single-purpose engines; smaller community than Neo4j or MongoDB.
Stardog
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.