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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

"The stability of Amazon Neptune is very good."
"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."
"Relational databases are never good at identifying patterns in graphs or other similar relationships, whereas Amazon Neptune is."
"MongoDB Atlas is a database that is quite fast, stable, and reliable."
"There are many valuable features, but scalability stands out. It can scale across zones. You can define multiple nodes. They have also partnered with AWS, offering great service with multiple features, including built-in backup, all under the same roof, without the need for external tools."
"I rate MongoDB Atlas a nine out of ten."
"The product provides quick transaction service, high availability, and efficient scalability features."
"What I found most valuable in MongoDB Atlas is its Elasticsearch feature. It also has high availability, so it's stable."
"Scalability is its most valuable feature, as it is pretty simple."
"It is nice because our developers create tables whenever they need to sync data."
"The most useful feature is the management of the backup."
 

Cons

"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."
"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."
"There are some features that could be useful for the customers I work with, which are related to migration from on-prem to the cloud."
"The web console isn't very intuitive, especially for large data."
"I am still new with it, but since I mentioned that I'm using this product for only the last six months and my experience with this product is good thus far, on a scale of one to ten, I would give MongoDB Atlas a six."
"I would like the solution to offer more integration capabilities since it is an area where the solution lacks."
"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."
"We need improved query performance."
"The UI can be difficult to understand."
"The price of the solution should be reduced."
 

Pricing and Cost Advice

"Microsoft Azure and Amazon AWS are on par for pricing and Google has been raising its prices."
"We pay for the license on a monthly basis. It's not cheap or expensive. For smaller companies, it's definitely expensive."
"The purchasing process through the AWS Marketplace was very good."
"The tool is free since it's an open-source product."
"MongoDB Atlas is not expensive, and since it's a cloud-based solution, you pay by usage."
"It is too expensive. They need to work on this."
"For our service, it was around 300 to 600 euros per month, which was acceptable for our customers."
"MongoDB Atlas is more cost-effective than Amazon DocumentDB. It also has a pay-as-you-go pricing model. Apart from the standard licensing cost, you must also pay to get MongoDB Atlas technical support, which is expensive."
"The solution is fairly priced."
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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.