Vendor comparison · August 18, 2026 · 10 min read
Neo4j vs Amazon Neptune.
A practical comparison for teams choosing a graph database for an enterprise knowledge graph or GraphRAG project. Both are excellent; they fit different organisations.
The short answer
Neo4j is the industry default for property graphs: mature, portable, and famously ergonomic thanks to Cypher. Amazon Neptune is the right choice when you're all in on AWS, want a fully managed service that integrates natively with IAM/VPC/CloudWatch, and value RDF+SPARQL support. If you need dual property graph + RDF, Neptune wins. If you need portability or the best out of the box DX, Neo4j wins.
Comparison at a glance
| Dimension | Neo4j | Amazon Neptune |
|---|---|---|
| Data model | Labelled Property Graph (native) | Property graph + RDF (dual mode) |
| Query languages | Cypher (primary), GraphQL, Gremlin | Gremlin, openCypher, SPARQL |
| Deployment | Self hosted, Neo4j AuraDB (managed), any cloud | AWS only managed service |
| Scaling model | Vertical + read replicas + Fabric for sharding | Vertical + read replicas, storage auto scales |
| Vector search | Native (Neo4j 5+ has vector indexes) | Native (Neptune Analytics) |
| Ecosystem tooling | Mature (Bloom, GDS, Aura, extensive drivers | AWS native) CloudWatch, IAM, VPC integration |
| Learning curve | Cypher is famously readable | Gremlin is powerful but not friendly to newcomers |
| Vendor lock | Portable: same DB runs anywhere | AWS locked |
| Pricing model | Per node licensing / Aura consumption | AWS instance + storage + I/O pricing |
When to pick Neo4j
- You want portability across on prem, AWS, GCP, Azure, and don't want to be AWS locked.
- Your team is new to graph and Cypher's readability will accelerate ramp up.
- You need the Graph Data Science library: Neo4j GDS is more mature for graph algorithms and embeddings.
- You want the option of managed (AuraDB) OR self hosted with the same engine.
- You're standardising on the property graph model and don't need RDF.
When to pick Amazon Neptune
- Your organisation is AWS first and IAM/VPC/CloudWatch integration is important.
- You need to store both property graph and RDF data in one system (dual mode).
- You want a fully managed service with zero cluster babysitting.
- Your semantic web / ontology heavy use cases (FIBO, industry ontologies) need first class SPARQL support.
- Cost predictability tied to the AWS bill matters more than portability.
The honest tradeoffs no vendor page will tell you
- Cypher on Neptune isn't Cypher on Neo4j. Neptune supports openCypher, but some Neo4j specific procedures and APOC functions don't translate.
- Neo4j GDS is a genuine differentiator if you need Louvain, PageRank, node2vec, or the built in ML pipelines. Neptune ML exists but is less broadly adopted.
- Neptune's SPARQL support is why FIBO and other ontology heavy shops often pick it. Neo4j supports RDF via the neosemantics plugin, but it's not first class.
- Managed service TCO looks lower until your query patterns produce high I/O on Neptune, at which point the bill can surprise you. Test with your actual workload.