Amazon Neptune Analytics vs Stardog
Amazon Neptune Analytics vs Stardog: side-by-side comparison of two knowledge-graph platforms systems — architecture, taxonomy, license, pricing, MCP/A2A support, and direct edges.
Cost & capability
| Amazon Neptune Analytics | Stardog | |
|---|---|---|
| Cost tier | mid | — |
Where they differ (10)
Rows where both sides have data and the values disagree — the shortlist of dimensions that actually distinguish these two systems.
| Amazon Neptune Analytics | Stardog | |
|---|---|---|
| Type | Vector + graph in one managed service | RDF semantic platform + Voicebox AI |
| Created | 2023-11 | 2010 |
| Pricing | Pay-per-use — billed per m-NCU-hour (1 m-NCU = 1 GB memory plus compute for 1 hour), $0.03 per m-NCU-hour in us-east-1 (16 m-NCU graph = $0.48/hour); paused graphs billed at 10% of compute | Stardog Free (renewable 1-year license, commercial use allowed, no HA/caching/backups); Enterprise on-prem and cloud quote-based |
| Funding | searched not found | $32M Series C (last known) · 2022-01 |
| Backend storage | custom (AWS Neptune managed) | custom (RDF triple store) |
| Deployment | Managed-only | Both |
| API surface | REST, openCypher, Gremlin, SPARQL, SDK: AWS SDKs | REST, SPARQL, SDK: Java, Python, JS |
| Multi-tenancy | hard-isolation | Per-database access control; on-prem / private-cloud / SaaS options |
| MCP | yes — official AWS Labs Amazon Neptune MCP server (openCypher queries, schema and status for Neptune Analytics graphs) | yes — official Stardog Cloud MCP server (stardog-union/stardog-cloud-mcp; remote setup in beta) |
| OpenTelemetry | first-class — CloudWatch / OTel | first-class — Prometheus + OTel |
At a glance
| Amazon Neptune Analytics | Stardog | |
|---|---|---|
| Section | Knowledge-graph platforms | Knowledge-graph platforms |
| Tier | T1 | T1 |
| Type | Vector + graph in one managed service | RDF semantic platform + Voicebox AI |
| Created | 2023-11 | 2010 |
| Pricing | Pay-per-use — billed per m-NCU-hour (1 m-NCU = 1 GB memory plus compute for 1 hour), $0.03 per m-NCU-hour in us-east-1 (16 m-NCU graph = $0.48/hour); paused graphs billed at 10% of compute | Stardog Free (renewable 1-year license, commercial use allowed, no HA/caching/backups); Enterprise on-prem and cloud quote-based |
| Funding | searched not found | $32M Series C (last known) · 2022-01 |
| Backend storage | custom (AWS Neptune managed) | custom (RDF triple store) |
| Deployment | Managed-only | Both |
| API surface | REST, openCypher, Gremlin, SPARQL, SDK: AWS SDKs | 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 — official AWS Labs Amazon Neptune MCP server (openCypher queries, schema and status for Neptune Analytics graphs) | 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 — CloudWatch / OTel | 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
Amazon Neptune Analytics
Pros: Managed graph database with vector + graph hybrid for AWS-native architectures; first-class integration with Bedrock and SageMaker.
Cons: AWS-only; vector + graph hybrid is newer than dedicated competitors; pricing complexity around graph queries.
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.