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Amazon Neptune Reviews

Vendor: Amazon Web Services (AWS)
4.3 out of 5
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What is Amazon Neptune?

Amazon Neptune is a highly reliable and scalable graph database service designed for applications that require fast, efficient querying of highly connected data. Its robust features support multiple graph models and development frameworks.

Get the Amazon Neptune Buyer's Guide and find out what your peers are saying about Amazon Neptune, MongoDB Enterprise Advanced, Microsoft Azure Cosmos DB and more!
Amazon Neptune is the #8 ranked solution in top Managed NoSQL Databases. PeerSpot users give Amazon Neptune an average rating of 8.6 out of 10. Amazon Neptune is most commonly compared to MongoDB Enterprise Advanced: Amazon Neptune vs MongoDB Enterprise Advanced. Amazon Neptune is popular among the large enterprise segment, accounting for 70% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a financial services firm, accounting for 20% of all views.
Buyer's Guide
Amazon Neptune
May 2026
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Amazon Neptune mindshare

As of May 2026, the mindshare of Amazon Neptune in the Managed NoSQL Databases category stands at 6.4%, down from 11.4% compared to the previous year, according to calculations based on PeerSpot user engagement data.
Managed NoSQL Databases Mindshare Distribution
ProductMindshare (%)
Amazon Neptune6.4%
Microsoft Azure Cosmos DB15.7%
MongoDB Atlas13.9%
Other64.0%
Managed NoSQL Databases

PeerResearch reports based on Amazon Neptune reviews

TypeTitleDate
CategoryManaged NoSQL DatabasesMay 5, 2026Download
ProductReviews, tips, and advice from real usersMay 5, 2026Download
ComparisonAmazon Neptune vs Microsoft Azure Cosmos DBMay 5, 2026Download
ComparisonAmazon Neptune vs Amazon DynamoDBMay 5, 2026Download
ComparisonAmazon Neptune vs MongoDB AtlasMay 5, 2026Download
Suggested products
TitleRatingMindshareRecommending
MongoDB Enterprise Advanced4.110.7%92%82 interviewsAdd to research
Microsoft Azure Cosmos DB4.115.7%95%109 interviewsAdd to research
 
 
Key learnings from peers
Last updated Mar 27, 2026

Valuable Features

  • "The stability of Amazon Neptune is very good."
  • "Amazon Neptune as a product by AWS is exceptional because it supports multiple graph models such as RDF and property graph, and it also has support for multiple querying languages such as Gremlin, SparkQL, and OpenCypher, making it very comprehensive in supporting every requirement we had at Zetta."
  • "Amazon Neptune as a product by AWS is exceptional because it supports multiple graph models such as RDF and property graph, and it also has support for multiple querying languages such as Gremlin, SparkQL, and OpenCypher, making it very comprehensive in supporting every requirement we had at Zetta."

Room for Improvement

Amazon Neptune requires more awareness due to its new technology. A visual representation of graphs is needed, similar to Neo4j. Improvements could include a UI that shows vertices and connections. Downtime during scalability, backward compatibility issues, and a small user community are concerns. Delving into documentation was time-consuming, with some sections providing incorrect information. More clarity in documentation and better technical support would enhance the overall experience.
  • "Amazon Neptune could improve by spreading more awareness for others to have an understanding of the solution because the technology is fairly new."
  • "We had a strict time constraint, and it took many sleepless nights to find information in the documentation."
  • "We had a strict time constraint, and it took many sleepless nights to find information in the documentation."

Pricing

  • "Microsoft Azure and Amazon AWS are on par for pricing and Google has been raising its prices."

Popular Use Cases

Amazon Neptune is primarily used for maintaining employee and customer hierarchies, tracking hierarchy history, real-time fraud detection, and managing microservice architecture traffic. Organizations use graph data with vertices and edges to represent complex relationships, like social networks, user data, and service requests. Data science jobs are triggered for real-time insights, helping organizations understand network interactions, service health, and request patterns, while switching from other databases like Neo4j due to cost considerations.

Deployment

Amazon Neptune's initial setup is considered straightforward by users, with AWS handling most aspects. Creating a Neptune database is possible with an AWS account and VPC. However, integrating with frameworks like Quarkus in Java can present challenges, though built-in SDKs ease integration for plain Java or Spring Boot applications. Deploying a new database often involves just a few clicks, making setup generally simple but potentially requiring extra methods for specific frameworks.

Stability

Amazon Neptune exhibits high stability. Many organizations found relational databases too restrictive and opted for this alternative. Users report no issues or outages, describing their experience as smooth and reliable. During POC trials, there were no downtime incidents, eliminating the need to test self-healing capacities.
These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.
Download our Amazon Neptune Buyer's Guide for additional reliable information.

Top industries

By visitors reading reviews
Financial Services Firm
20%
University
13%
Computer Software Company
11%
Insurance Company
7%
Construction Company
6%
Media Company
5%
Transportation Company
5%
Retailer
4%
Manufacturing Company
4%
Pharma/Biotech Company
2%
Outsourcing Company
2%
Government
2%
Religious Institution
2%
Healthcare Company
2%
Educational Organization
2%
Wholesaler/Distributor
1%
Energy/Utilities Company
1%
Hospitality Company
1%
Logistics Company
1%
Marketing Services Firm
1%
Non Profit
1%
Performing Arts
1%
Recruiting/Hr Firm
1%
Venture Capital & Private Equity Firm
1%
Comms Service Provider
1%

Compare Amazon Neptune with alternative products

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Learn more about Amazon Neptune

Neptune leverages graph query languages like Gremlin and SPARQL, making it a versatile choice for businesses needing to efficiently manage and analyze relationships among data points. With seamless integration into AWS infrastructure, it supports complex applications in social networking, fraud detection, and recommendation engines. Its capability to handle billions of relationships allows developers to build sophisticated models for various industry applications.

What are the most important features of Amazon Neptune?
  • Multi-Model Support: Enables both RDF/SPARQL and Property Graph/Gremlin allowing flexibility in database design.
  • Serverless Architecture: Ensures scalability and optimized resource usage by automatically scaling to meet demands.
  • High Availability and Durability: Provides automated backups and replication across multiple zones to secure data integrity and availability.
  • Advanced Security: Features encryption at rest and in transit, along with network isolation and fine-grained access control.
What benefits or ROI should users look for in reviews?
  • Reduced Complexity: Simplifies managing graph data without the need for manual provisioning and infrastructure management.
  • Cost Efficiency: Pay-as-you-go pricing model allows for cost-effective usage.
  • Quick Deployment: Accelerates project timelines with easy integration into AWS services, reducing time to market.
  • Improved Query Performance: Speeds up finding insights due to optimized graph traversal techniques.

Amazon Neptune is widely used in industries like financial services for fraud detection and risk assessments by quickly identifying patterns and anomalies. In retail, it enhances product recommendations and customer interaction analysis. Healthcare sectors implement it for patient data management and insights generation to improve care coordination and outcomes.

Amazon Neptune customers

Intuit, Pearson, Samsung, Ignition One, Lifeomic, Blackfynn, Paysense

Related questions

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Amazon Neptune Reviews Summary
Author infoRatingReview Summary
Back End Developer at Zeta4.0I used Amazon Neptune to monitor service traffic at Zetta and found its multi-graph model and query language support excellent, though limited community support and incomplete documentation made adoption time-consuming during our strict deadlines.
Principal Engineer at Paynearby4.5I switched from Neo4j to Amazon Neptune to manage employee and customer hierarchy due to cost concerns. However, Neptune lacks a visual graph representation, which makes analyzing connections in the graph database less intuitive compared to Neo4j.
Staff Software Engineer at a tech vendor with 1,001-5,000 employees4.0I used Amazon Neptune at a gaming company for real-time fraud detection with graph data. Jupyter Notebooks integration was valuable, though improvements are needed for UI visualization and downtime during scaling. We previously used RDS and compared it to Neo4j on AWS.
Senior Database Administrator at Summa Health System4.5I find Amazon Neptune a stable, scalable graph database excellent for identifying complex patterns like fraud, where relational databases fail. Setup is straightforward, but it needs more community awareness as the technology is new.