HPE Data Fabric vs MongoDB Enterprise Advanced comparison

The compared Hewlett Packard Enterprise and MongoDB solutions aren't in the same category. Hewlett Packard Enterprise is ranked #4 in H , and holds a 10.5% mindshare in the category. MongoDB is ranked #1 in ND , with an average rating of 8.4, and holds a 13.3% 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

1,828 Views
1,481 Comparison Views

100% willing to recommend

MongoDB Enterprise Advanced

Read 82 MongoDB Enterprise Advanced reviews

9,029 Views
4,605 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: April 2026).

Buyer's Guide

Hadoop

April 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 (4th)

MongoDB Enterprise Advanced

Average Rating

8.2

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Open Source Databases (5th), NoSQL Databases (1st), 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 10.5%, down 15.2% compared to last year.
MongoDB Enterprise Advanced, on the other hand, focuses on NoSQL Databases, holds 13.3% mindshare, down 17.4% since last year.

Hadoop Mindshare Distribution
Product	Mindshare (%)
HPE Data Fabric	10.5%
Cloudera Distribution for Hadoop	14.8%
Apache Spark	13.6%
Other	61.1%

Hadoop

NoSQL Databases Mindshare Distribution
Product	Mindshare (%)
MongoDB Enterprise Advanced	13.3%
Redis	8.6%
Cassandra	8.2%
Other	69.9%

NoSQL Databases

Featured Reviews

Hamid M. Hamid

Data architect at Banking Sector

A stable and scalable tool that serves as a great database

The initial setup of HPE Ezmeral Data Fabric is easy. I am not sure how long it took to deploy HPE Ezmeral Data Fabric, but I haven't heard about any disadvantages when it comes to the time taken for the deployment. I remember that one of our company's clients who had purchased the product never mentioned the product's setup phase being complex. One of the drawbacks with HPE Ezmeral Data Fabric stems from the fact that the product's upgrade was not straightforward, and it was a complex process since one of the teams in my company who deals with the tool found the upgrade part to be tough. The solution is deployed on an on-premises model. My company has two dedicated staff members to look after the deployment and maintenance phases of HPE Ezmeral Data Fabric.

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Fabien GOUINEAU

Architecte Cloud at Visiativ SA

Offers reliable engine for legacy needs but requires enhanced cost management and AI features

While MongoDB is a good product, it is also an expensive product for support, and its scalability is acceptable, but the big problem with MongoDB is the cost. For security in MongoDB, we work with encrypted databases by default, but we have not contracted the security options in our contract because it is too expensive, so we only implement encrypted databases without the security pack, which is very expensive for us; in security, we are at the first steps, just using encrypted databases. I think additional features needed in MongoDB include perhaps vector databases, as I think they are not supported right now.

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

"I highly recommend MapR."

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

"Outside of human error, MapR is probably the most stable of the major releases."

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

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

"MapR is a great distribution, although I have limited experience with other distributors."

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

"HPE Ezmeral Data Fabric can be accessed from any namespace globally as you would access it from a machine using an NFS."

More HPE Data Fabric pros

"It is easy to use."

"We haven't had any issues with stability."

"We decided to work with MongoDB as its interface is easier to understand and more universal."

"Its flexibility, and cost. It is reasonably priced."

"It is really a pretty easy product to use; it's very reliable, it's proven."

"The solution is user-friendly with a good object retrieval feature."

"I value the API integrations."

"MongoDB is more secure than similar databases."

More MongoDB Enterprise Advanced pros

Cons

"I'd say we've had issues with pricing."

"Installations and setups are still a bit cryptic and can be improved."

"The UI for administration still has a lot of manual work to set up the cluster and get it running."

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

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

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

"One weakness for MapR is the Kerberos support."

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

More HPE Data Fabric cons

"The dashboard is an area of concern in the solution where improvements are required."

"Its security features can be better. Sometimes, my higher authority says that we are not going to use MongoDB because it doesn't provide that much security for the RDBMS or relational data that we use for transactions."

"The documentation for MongoDB is not very good and should be improved."

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

"The auto transaction feature is something that I found a little bit problematic. If we want to run two or three transactions at a time, we get write conflicts."

"It is important to note that MongoDB has limitations since it can only be used for specific use cases. For example, for master data, I would want to pick keys using an RDBMS, but for attachments, I would choose MongoDB."

"At the start, connecting to the database via Compass or through a direct ID was a challenge."

"It isn't easy to recognize entities with MongoDB."

More MongoDB Enterprise Advanced cons

Pricing and Cost Advice

"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."

"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 an enterprise license and it could be cheaper. We are using the free open source version."

"At the moment, all customers are using the community version."

"I currently use the solution's community edition which is free."

"The product is affordable."

"This is an open-source solution."

"MongoDB is not expensive."

"MongoDB is a bit expensive compared to its competitors."

"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."

More MongoDB Enterprise Advanced pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Construction Company

11%

Comms Service Provider

Healthcare Company

Financial Services Firm

14%

Manufacturing Company

Computer Software Company

University

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

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What do you like most about MongoDB?

MongoDB's approach to handling data in documents rather than traditional tables has been particularly beneficial.

See all answers

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

Comparisons

Cloudera Distribution for Hadoop vs HPE Data Fabric

Compared 17% of the time

Cloudera Data Platform vs HPE Data Fabric

Compared 13% of the time

IBM Spectrum Computing vs HPE Data Fabric

Compared 10% of the time

IBM Analytics Engine vs HPE Data Fabric

Compared 10% of the time

More HPE Data Fabric Competitors

MongoDB Atlas vs MongoDB Enterprise Advanced

Compared 6% of the time

Microsoft Azure Cosmos DB vs MongoDB Enterprise Advanced

Compared 5% of the time

InfluxDB vs MongoDB Enterprise Advanced

Compared 5% of the time

PostgreSQL vs MongoDB Enterprise Advanced

Compared 5% of the time

Couchbase Enterprise vs MongoDB Enterprise Advanced

Compared 4% of the time

More MongoDB Enterprise Advanced Competitors

Product Reports

Buyer's Guide

HPE Data Fabric

May 2026

Download HPE Data Fabric product report

Buyer's Guide

MongoDB Enterprise Advanced

April 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

Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop. Updated: April 2026.

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