HPE Data Fabric vs MongoDB Enterprise Advanced comparison

Why PeerSpot?

The compared Hewlett Packard Enterprise and MongoDB solutions aren't in the same category. Hewlett Packard Enterprise is ranked #5 in H , and holds a 9.2% mindshare in the category. MongoDB is ranked #2 in ND , with an average rating of 8.1, and holds a 11.3% mindshare. Additionally, 100% of Hewlett Packard Enterprise users are willing to recommend the solution, compared to 92% of MongoDB users who would recommend it.

HPE Data Fabric

Read 12 HPE Data Fabric reviews

2,863 Views
2,376 Comparison Views

100% willing to recommend

MongoDB Enterprise Advanced

Read 82 MongoDB Enterprise Advanced reviews

14,325 Views
6,876 Comparison Views

92% willing to recommend

HPE Data Fabric

MongoDB Enterprise Advanced

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between HPE Data Fabric and MongoDB Enterprise Advanced based on real PeerSpot user reviews.

Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop.

To learn more, read our detailed Hadoop Report (Updated: October 2026).

Buyer's Guide

Hadoop

October 2026

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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

HPE Data Fabric

Average Rating

8.0

Reviews Sentiment

6.1

Number of Reviews

Ranking in other categories

Hadoop (5th)

MongoDB Enterprise Advanced

Average Rating

8.2

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Open Source Databases (9th), NoSQL Databases (2nd), Managed NoSQL Databases (4th)

Mindshare comparison

HPE Data Fabric and MongoDB Enterprise Advanced aren’t in the same category and serve different purposes. HPE Data Fabric is designed for Hadoop and holds a mindshare of 9.2%, down 14.5% compared to last year.
MongoDB Enterprise Advanced, on the other hand, focuses on NoSQL Databases, holds 11.3% mindshare, down 16.2% since last year.

Hadoop Mindshare Distribution
Product	Mindshare (%)
HPE Data Fabric	9.2%
Cloudera Distribution for Hadoop	14.6%
Apache Spark	14.4%
Other	61.800000000000004%

Hadoop

NoSQL Databases Mindshare Distribution
Product	Mindshare (%)
MongoDB Enterprise Advanced	11.3%
Cassandra	8.8%
Redis	7.8%
Other	72.1%

NoSQL Databases

Featured Reviews

Arnab Chatterjee

Regional Head of Data and Application Platform at a financial services firm with 10,001+ employees

It's flexible and easily accessible across multiple locations, but the upgrade process is complicated

Upgrading Ezmeral to a new version is a pain. They're trying to make the solution more container-friendly, so I think they're going in the right direction. The only problem we've had in the past was the upgrades. The process isn't smooth due to how the Red Hat operating system upgrades currently work. They're transforming their host stack to increase cloud readiness and edge compute capability. HPE is transitioning from a standard data-driven approach to one powered by AI analytics. That's something they have released very recently. I haven't tried that, but it will probably make things easier. The ability to adapt Ezmeral to the public cloud is probably missing. I've heard that they're getting leaner. However, it doesn't have a clear managed services offering for you if you want to deploy this stack on the cloud. That's a problem. This probably won't meet your needs if you require consistency across on-prem and the cloud. It's not Ezmeral's fault. None of the products would fit the bill. Cloud offerings are biased towards their own implementation. It's a general issue on most big data platforms. They're already working towards that, but it hasn't been released.

Read full review

Romel Jr Zerna

Software Engineer at Pioneer Dev AI

Document data has streamlined prototyping and now supports secure cloud deployments

I use the cloud version of the product. MongoDB Enterprise Advanced is from MongoDB, though I also use DigitalOcean as a third-party provider. Maybe it's all more about preferences. I think MongoDB Enterprise Advanced has weak support on the ORM side, particularly if you're using Prisma. I think mostly the focus now on the tools we have is PostgreSQL. MongoDB Enterprise Advanced is not really used that much on our side for production. It's not really a weak point. It's more of a double-edged sword. If you like document-based management databases and you don't want any migrations, then you go to MongoDB Enterprise Advanced. If you want more secure databases, then you use SQL. On the account management and the way you secure the connection strings, I have utilized advanced security features with MongoDB Enterprise Advanced. I think it's very expensive on the Atlas enterprise side. But if you go to other providers of MongoDB Enterprise Advanced, such as DigitalOcean, it may be harder to set up, but they can save you money.

Read full review

Quotes from Members

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

Pros

"This product enabled us opening up endless possibilities in data analytics, IOE/IOT, and predictive analysis."

"My first choice is MapR, as it is more adaptable to different contexts, and it could be customized in some way to fit the different needs, and this is my first choice and my first advice to people who ask me about this particular platform."

"Our customer purchased a paid support service and so far MapR has addressed our issues well."

"I highly recommend MapR."

"It is a stable solution...It is a scalable solution."

"The model creation was very interesting, especially with the libraries provided by the platform."

"The fact that the heavy computation is required on Big Data can be distributed across many nodes in a cluster, makes this solution a winner."

"My customers find the product cheaper compared to other solutions. The previous solution that we used did not have unified analytics like the runtime or the analog."

More HPE Data Fabric pros

"The geospatial index feature is useful for dealing with latitude and longitude data."

"It facilitates the generation of heatmaps for graphical data analysis."

"My advice for anybody who is considering MongoDB is that when we want to have flexibility in storing our data, I recommend using it."

"The fact is all of our users are happy with the stability and quick response times our solutions have."

"The stability of the solution is very good, there are no bugs or glitches, it doesn't crash or freeze, and it's pretty good overall."

"I value the API integrations."

"MongoDB is easy to use."

"The most valuable feature is the geometric information done with GeoJSON."

More MongoDB Enterprise Advanced pros

Cons

"It would be nice to have new developments in the Apache space (Spark, Storm, etc.)."

"One weakness for MapR is the Kerberos support."

"Having the ability to extend the services provided by the platform to an API architecture, a micro-services architecture, could be very helpful."

"The biggest drawback is that it has vendor locking."

"HPE Ezmeral Data Fabric is not compatible with third-party tools."

"It'd like to see file system auditing, data encryption, and certification of other vendors' tools."

"The product is not user-friendly."

"The interface part, what I'm calling the integration part, could be improved."

More HPE Data Fabric cons

"The improvements could be made to intelligence to detect disk storage and prevent MongoDB from crashing."

"I'd like to see an ID generator. It's very technical but I don't think it has one, so we have to go to great lengths to work around that."

"The performance of the solution could be improved."

"A normal Oracle or database tester will take some time to gear up to MongoDB because the way of writing queries is different in MongoDB. There should be some kind of midway where a person who is coming from an Oracle background can write a query and get a response by using something like a select * statement or other such things. There should be some way for MongoDB to interpret these commands rather than making a person learn MongoDB commands and writing them. I struggled while writing these MongoDB commands. I had not seen such queries before. It was pretty difficult to get them. This is one of the areas where it would help from the improvement standpoint."

"I would like to see the scalability and security improved."

"The solution should have better integration."

"Data encryption is possible using third-party tools but they should have their own encryption capability built-in to this solution."

"MongoDB can improve large-size video or media frame operations. There are a lot of customers who want to upload media frames and video games but there is some difficulty. In MongoDB, we are looking out for solutions that are for large-size media files that can be saved and navigated efficiently."

More MongoDB Enterprise Advanced cons

Pricing and Cost Advice

"HPE is flexible with you if you are an existing customer. They offer different models that might be beneficial for your organization. It all depends on how you negotiate."

"There is a need for my company to pay for the licensing costs of the solution."

"The tool's price is cheap and based on a usage basis. The solution's licensing costs are yearly and there are no extra costs."

"MongoDB's pricing is not reasonable, but it is not as expensive as the others."

"There is an annual subscription for the use of this solution."

"If you want support with the solution you will need to purchase a license and not use the open-source version. The license is a little expensive."

"I only used the open-source version."

"MongoDB is an open-source solution."

"You only have to pay for the paid version, not the open-source version."

"The pricing is favorable if you opt to install MongoDB on an Amazon EC2 instance as you won't have to pay for the extra Atlas services and can instead manage the scaling yourself. This allows for a cost-effective solution and using MongoDB on a small scale, I have been able to utilize it for free."

"The solution is open source, so it is free."

More MongoDB Enterprise Advanced pricing and cost advice

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Top Industries

By visitors reading reviews

Construction Company

17%

Financial Services Firm

15%

Comms Service Provider

10%

Healthcare Company

10%

Financial Services Firm

14%

Manufacturing Company

Outsourcing Company

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	4
Large Enterprise	7

By reviewers
Company Size	Count
Small Business	36
Midsize Enterprise	13
Large Enterprise	39

Questions from the Community

Ask a question

Earn 20 points

What is your experience regarding pricing and costs for MongoDB?

I think it depends on the provider. For example, on DigitalOcean, they have strict routing. You have to whitelist an IP address, or you risk getting DDoS. Then if you're going for the Atlas one tha...

See all answers

What needs improvement with MongoDB?

I don't really have a deep dive into it, but I see that MongoDB Enterprise Advanced has RAG and Vertex support. However, we really didn't use it because I think one thing also is that Prisma, the O...

See all answers

What is your primary use case for MongoDB?

A typical use case for MongoDB Enterprise Advanced is mostly for the database, storing our data.

See all answers

Comparisons

Cloudera Distribution for Hadoop vs HPE Data Fabric

Compared 17% of the time

IBM Spectrum Computing vs HPE Data Fabric

Compared 11% of the time

Amazon EMR vs HPE Data Fabric

Compared 11% of the time

IBM Analytics Engine vs HPE Data Fabric

Compared 11% of the time

DataStax Enterprise vs HPE Data Fabric

Compared 2% of the time

More HPE Data Fabric Competitors

MongoDB Atlas vs MongoDB Enterprise Advanced

Compared 6% of the time

PostgreSQL vs MongoDB Enterprise Advanced

Compared 4% of the time

Redis vs MongoDB Enterprise Advanced

Compared 4% of the time

InfluxDB vs MongoDB Enterprise Advanced

Compared 4% of the time

MySQL vs MongoDB Enterprise Advanced

Compared 4% of the time

More MongoDB Enterprise Advanced Competitors

Product Reports

Buyer's Guide

HPE Data Fabric

October 2026

Download HPE Data Fabric product report

Buyer's Guide

MongoDB Enterprise Advanced

October 2026

Download MongoDB Enterprise Advanced product report

Also Known As

MapR, MapR Data Platform

No data available

Overview

HPE Data Fabric delivers robust data management with features like multi-tenancy, security, and ease of configuration. It supports high performance and unified analytics, making it a reliable choice for organizations looking to manage extensive data efficiently.

HPE Data Fabric provides a comprehensive data management platform with clustered node distribution and no single point of failure, ensuring high availability. Its compatibility with MapR-DB and NFS functionality allows integration with existing systems. Although there are challenges with third-party tool compatibility and upgrades, it supports big data initiatives by acting as both a database and messaging layer. Users benefit from bundled ecosystem support and simplified administration, enhancing usability across multiple teams and locations.

What features make HPE Data Fabric valuable?

Multi-tenancy: Supports multiple users or tenants securely.
Clustered Node Distribution: Distributes data across nodes for reliability.
POSIX Compliance: Compatibility with POSIX standards for ease of integration.
NFS Functionality: Facilitates network-based file sharing.
Unified Analytics: Provides integrated data analysis capabilities.

Why consider HPE Data Fabric in reviews?

Reliability: No single point of failure, ensuring consistent performance.
Cost Efficiency: Offers cost-effective data management solutions.
High Availability: Provides resilient storage and service availability.
Ease of Configuration: Streamlines administrative tasks with UI-driven tools.

Organizations in sectors such as finance, healthcare, and logistics use HPE Data Fabric to manage large volumes of data efficiently. Its role in supporting distributed processing and acting as a NoSQL storage solution enables these industries to leverage big data for enhanced operational insights and decision-making capabilities. The inclusion of AI tools further expands its utility, facilitating advanced data environments that are cost-effective and scalable for growing organizational demands.

Hewlett Packard Enterprise

MongoDB Enterprise Advanced is a comprehensive platform renowned for its scalability, user-friendliness, and high performance, underpinned by its flexible document-based storage and open-source model. JSON compatibility, clustering, and security elevate its standing among professionals.

The platform facilitates efficient data management through developer-friendly tools and a strong aggregation framework. MongoDB’s no-schema requirement, supported by community expertise, underlines its adaptability. While its sharding capabilities and affordably support large data volumes, there are aspects such as security enhancement and enterprise tool integration that need attention. Indexing and query optimization pose challenges, alongside high costs. Improvements in analytics and UI could advance its infrastructure further.

What are the key features of MongoDB Enterprise Advanced?

Scalability: Dynamic adjustments to workloads with ease.
JSON Compatibility: Seamless data structuring with JSON support.
Clustering: Enhanced data management through robust clustering.
Security Integration: Built-in security measures for data protection.
Sharding: Efficient distribution of large datasets.

What benefits should users look for in reviews?

Document-Based Storage: Flexibility in managing varied data types.
Open-Source: Access to a broad community and resources.
Low-Cost Implementation: Economic efficiency in deployment.
Scalability: Supports the growth of data without sacrificing performance.

Industries leverage MongoDB Enterprise Advanced for significant roles in data storage within IoT platforms, healthcare apps, public service monitoring, and big data analytics. Companies in logistics and telecommunications find it instrumental for business process management and video content management, benefiting from its seamless integration and unstructured data support.

MongoDB

Sample Customers

Valence Health, Goodgame Studios, Pico, Terbium Labs, sovrn, Harte Hanks, Quantium, Razorsight, Novartis, Experian, Dentsu ix, Pontis Transitions, DataSong, Return Path, RAPP, HP

Facebook, MetLife, City of Chicago, Expedia, eBay, Google

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