TL;DR - Amazon Neptune
- Amazon Neptune is a fully managed graph database service for building applications with connected data
- It supports both property graph and RDF models with Apache TinkerPop and SPARQL query languages
- Pricing based on instance size starting around $0.10/hour for the smallest instance
Pricing: Paid only
Best for: Enterprises & professionals
Score: 82/100
Pricing Plans
free trialMost Popular
On-Demand
$0.1/per db.r5.large hour
Pay-as-you-go
- Graph database
- Auto-scaling
- High availability
- All features
Serverless
Usage-based
Auto-scaling
- NCU-based pricing
- Scale to zero
- No capacity planning
About Amazon Neptune
Amazon Neptune is a graph database for connected data. When relationships between entities matter as much as the entities themselves—social networks, fraud detection, recommendations—Neptune handles queries that would crush relational databases.
Both property graph and RDF models are supported, so you can choose the approach that fits your data. Fully managed on AWS means no database administration headaches.
Organizations modeling complex relationships find Neptune makes queries natural that would require painful SQL joins. The graph model matches how you actually think about connected data.
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Amazon Neptune FAQ
Neptune is AWS's managed graph database. Supports both property graphs (Gremlin) and RDF (SPARQL). Good for highly connected data like social networks, recommendations, and fraud detection.
Instance-based pricing starting around $0.10/hour for smallest instance. Plus storage ($0.10/GB/month) and I/O costs. No free tier - estimate costs carefully before using.
Neptune for relationship-heavy data with complex traversals. DynamoDB for simple key-value access at scale. Neptune is expensive for simple use cases; DynamoDB can't do graph queries.
Neptune supports Gremlin (TinkerPop) for property graphs and SPARQL for RDF data. OpenCypher support added in 2021. Choose based on your data model and team expertise.
Neptune Serverless is available for auto-scaling capacity. Pay only for what you use. Good for variable workloads but can be expensive for steady high usage.