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Amazon Neptune vs MongoDB Atlas comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 11, 2026

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Amazon Neptune
Ranking in Managed NoSQL Databases
8th
Average Rating
8.6
Reviews Sentiment
4.5
Number of Reviews
4
Ranking in other categories
No ranking in other categories
MongoDB Atlas
Ranking in Managed NoSQL Databases
3rd
Average Rating
8.4
Reviews Sentiment
7.0
Number of Reviews
52
Ranking in other categories
Database as a Service (DBaaS) (3rd), Database Management Systems (DBMS) (2nd), AI Software Development (4th)
 

Mindshare comparison

As of June 2026, in the Managed NoSQL Databases category, the mindshare of Amazon Neptune is 6.1%, down from 10.6% compared to the previous year. The mindshare of MongoDB Atlas is 14.4%, up from 6.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Managed NoSQL Databases Mindshare Distribution
ProductMindshare (%)
MongoDB Atlas14.4%
Amazon Neptune6.1%
Other79.5%
Managed NoSQL Databases
 

Featured Reviews

Reviewer3028812 - PeerSpot reviewer
Back End Developer at Zeta
Multiple graph models and languages support lead to efficient use, yet community growth brings challenges
The onboarding part and documentation where we could ideally use Amazon Neptune is excellent. Amazon Neptune as a product by AWS is exceptional because it supports multiple graph models such as RDF and property graph. It also has support for multiple querying languages such as Gremlin, SparkQL, and OpenCypher. It is very comprehensive in supporting every requirement we had at Zetta. Amazon Neptune's best features include its multiple servers, each supporting different languages such as OpenCypher, SparkQL, and RDF. For the same RDF graph or property graph, we could use multiple languages to query on different servers. This is exceptional because we have one graph DB with two endpoints exposed where we could interact with different languages on the same graph. Additionally, Amazon has a Sagemaker Jupyter Notebook which interacts with the Amazon Neptune database itself, providing a clean UI for representing nodes since the Jupyter Notebook has predefined graph representation capabilities through queries.
Varuns Ug - PeerSpot reviewer
Senior Software Developer at NIT
Flexible document workflows have accelerated schema changes and simplified evolving data models
MongoDB Atlas currently has almost all the features we require, but there are some points where I see certain improvements. One area is cost visibility and optimization. Since pricing is largely based on storage and cluster size, it can sometimes be difficult to predict or optimize cost without deeper insights. More granular cost breakdowns or recommendations would be helpful. Another area I can mention is performance tuning transparency. While MongoDB Atlas provides monitoring and suggestions, debugging deeper issues like slow queries, index efficiency, or shard imbalance can sometimes require more control or visibility. Cost optimization, deeper performance insight, and easier scaling decisions would make MongoDB Atlas even more powerful. A couple of additional areas where MongoDB Atlas could improve are integrations and developer experience. For integrations, while MongoDB Atlas supports major cloud providers and tools, deeper and more seamless integration with observability patterns would make troubleshooting distributed systems easier. On the documentation side, while it is generally good, some advanced topics like sharding strategies, performance tuning, and real-world scaling patterns could benefit from more practical guidance. Additionally, a better local-to-cloud development experience, making it easier to replicate production-like MongoDB Atlas environments locally, would help developers test performance and scaling scenarios more efficiently.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Relational databases are never good at identifying patterns in graphs or other similar relationships, whereas Amazon Neptune is."
"The initial setup is actually simple."
"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."
"The stability of Amazon Neptune is very good."
"It enables us to get work done quickly and get to our data."
"It has a flexible integration with our easy API."
"The initial setup of MongoDB Atlas is straightforward...It is a scalable solution."
"This solution is very helpful due to its ease of use."
"For security reasons, I prefer MongoDB Atlas. It supports role-based access control, so you have an entity for each individual."
"The most valuable feature is the schemaless architecture."
"The stability and performance are great. The high availability feature is great. Moreover, I am happy with the automated backup and restore functionality."
"My company is interested in putting out products that are reliable for our customers, which we can monitor easily, and we also want them to be easy to install and deploy, which is why I am happy with this one."
 

Cons

"In my scenario, the integration wasn't easy because ................in Java."
"We had a strict time constraint, and it took many sleepless nights to find information in the documentation."
"Amazon Neptune could improve by spreading more awareness for others to have an understanding of the solution because the technology is fairly new. The developer community and larger community do not understand it yet."
"I would like a better dashboard. It could be made a bit more user friendly."
"The cost needs improvement."
"The UI is not currently designed in a manner to make it possible for a non-technical person or a layman to update the database easily."
"I would like a more comprehensive dashboard."
"From the scalability point of view, when we shard the database it creates a replica set of each shard and that will increase the cost."
"The web console isn't very intuitive, especially for large data."
"Going forward, we would like to have pure AWS Cloud (native) storage instead regular storage on the AWS integration side."
"We had some edge cases where scalability was an issue where a node went offline, and we had to deal with that."
 

Pricing and Cost Advice

"Microsoft Azure and Amazon AWS are on par for pricing and Google has been raising its prices."
"Comparing the price between the MongoDB and Microsoft SQL Server, we are using the enterprise edition of Microsoft SQL Server, which is more expensive than MongoDB."
"Pricing could always be better."
"It is too expensive. They need to work on this."
"I have seen the cost, and it was pretty cheap."
"For our service, it was around 300 to 600 euros per month, which was acceptable for our customers."
"The solution is expensive overall. It does not require a license but if you want the support then you will need to purchase the license. They use a pay-as-you-go model and you are able to receive some discounts by making longer usage commitments."
"The price of MongoDB Atlas is highly expensive to use and maintain. They are taking advantage of the users with such a high price."
"We're currently using the Atlas for the night and don't require a license. However, it can be a problem if you want to use their enterprise environment. Then you need to purchase the license."
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Top Industries

By visitors reading reviews
Financial Services Firm
19%
University
12%
Computer Software Company
10%
Construction Company
10%
Manufacturing Company
14%
Financial Services Firm
12%
Construction Company
10%
Computer Software Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business24
Midsize Enterprise11
Large Enterprise23
 

Questions from the Community

What is your experience regarding pricing and costs for Amazon Neptune?
The cost aspects were managed by our SRE team who provisioned the instances. The pricing structure is similar to how EC2 instance pricing varies. I was informed that it was somewhat expensive, thou...
What needs improvement with Amazon Neptune?
The main issue was the limited community of Amazon Neptune users, which meant everything needed to be explored independently. Although this was adventurous, it required more time investment in the ...
What is your primary use case for Amazon Neptune?
We managed traffic at Zetta, and traffic would be moving between multiple services in our microservice architecture. Because of this setup, we were using Amazon Neptune to understand how many reque...
What is your experience regarding pricing and costs for MongoDB Atlas?
Pricing-wise, MongoDB Atlas has a pay-as-you-go strategy. The documentation for MongoDB is very good; I have learned multiple things through reading it. The free tier is M0 for $0, which is suitabl...
What needs improvement with MongoDB Atlas?
MongoDB Atlas currently has almost all the features we require, but there are some points where I see certain improvements. One area is cost visibility and optimization. Since pricing is largely ba...
What is your primary use case for MongoDB Atlas?
In my day-to-day work, I use MongoDB Atlas primarily for storing and querying semi-structured or dynamic data where schema flexibility is important, as I work extensively on schema design, indexing...
 

Also Known As

No data available
Atlas, MongoDB Atlas (pay-as-you-go)
 

Overview

 

Sample Customers

Intuit, Pearson, Samsung, Ignition One, Lifeomic, Blackfynn, Paysense
Wells Fargo, Forbes, Ulta Beauty, Bosch, Sanoma, Current (a Digital Bank), ASAP Log, SBB, Zebra Technologies, Radial, Kovai, Eni, Accuhit, Cognigy, and Payload.
Find out what your peers are saying about Amazon Neptune vs. MongoDB Atlas and other solutions. Updated: June 2026.
900,747 professionals have used our research since 2012.