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 #4 in H , and holds a 9.6% mindshare in the category. MongoDB is ranked #2 in ND , with an average rating of 8.4, and holds a 12.7% 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

2,549 Views
2,116 Comparison Views

100% willing to recommend

MongoDB Enterprise Advanced

Read 82 MongoDB Enterprise Advanced reviews

13,004 Views
6,242 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: September 2026).

Buyer's Guide

Hadoop

September 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 (8th), 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 9.6%, down 14.2% compared to last year.
MongoDB Enterprise Advanced, on the other hand, focuses on NoSQL Databases, holds 12.7% mindshare, down 16.7% since last year.

Hadoop Mindshare Distribution
Product	Mindshare (%)
HPE Data Fabric	9.6%
Cloudera Distribution for Hadoop	14.4%
Apache Spark	14.1%
Other	61.9%

Hadoop

NoSQL Databases Mindshare Distribution
Product	Mindshare (%)
MongoDB Enterprise Advanced	12.7%
Cassandra	8.3%
Redis	8.0%
Other	71.0%

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.

Read full review

Anand Bandi

Co-Founder at Vsigma IT Labs Pvt Ltd

Have managed customer transaction data efficiently and supported high-demand workloads with reliable performance

The integration between data warehouse could be improved. Nowadays, a lot of data is getting generated, so certain ETL flexible scripts with backend database integrations would be an improvement I could see. I will not be able to clearly say there is currently a deficiency there. All our DBs are integrated with a backend data warehouse, not necessarily AWS. When third-party data warehouses are integrated, we are seeing some ETL job performance issues. It is a one-off scenario so we have not thoroughly done any troubleshooting on that. It could be platform or third-party related issue. From the AWS standpoint, if robust integration and data warehouse integration specific tools are added in the advanced suite, that would definitely be helpful.

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

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

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

"Initial setup is rather straightforward thanks to detailed documentation covering all the bases."

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

"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."

"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 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."

More HPE Data Fabric pros

"The solution is stable and the performance is good."

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

"We capture more than 30 million records every week in IoT NS and MongoDB has been serving us well so far, making it easier to maintain the data with its document-based storage."

"For people or businesses that are currently trying to put their feet in the industry, it is a good thing to start their career with MongoDB."

"The most valuable features of MongoDB include the flexible schema for storing data, its replication capabilities with high availability through a replica set setup, and horizontal scalability using sharding."

"MongoDB is a solution that I can recommend because we have realized good benefits from it."

"The installation is very stable."

"The most valuable features of MongoDB are we have a lot of documentation and SQL-based applications that run on it."

More MongoDB Enterprise Advanced pros

Cons

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

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

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

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

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

"The product is not user-friendly."

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

"The deployment could be faster. I want more support for the data lake in the next release."

More HPE Data Fabric cons

"Lacks sufficient scalability and elasticity."

"The solution can be a bit tough to set up if you don't have knowledge about how the database works."

"From my point of view, they need a totally free IDE to work at high levels."

"MongoDB should better support small and medium companies. There are a lot of clients out there that are interested, however, they need something lighter and less complex and something not so expensive upfront."

"There are some problems with bugs appearing in sharding when the data is too high."

"There was a need for integrating relational database capabilities, however, MongoDB has introduced a relational converter that allows conversion between SQL and NoSQL."

"It could be much more flexible like SequoiaDB. I would like to see more flexibility in the next release, especially when working with Microsoft Windows. A lot of people struggle with MongoDB because of their Windows versions. But Linux is faultless and mostly runs nicely."

"I think it would be good to have more search options such as an index resource. This will provide more options and resources to do advance searches."

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."

"I believe that MongoDB is free."

"MongoDB is a free solution. We wanted to have high availability and the subscription cost was quite expensive because the basic one is free and then when you want to have some other replications or other features you will need to pay money. Overall the solution is expensive."

"It is rather expensive."

"I don't know, but I have heard from people who procure it that it is much cheaper than Oracle."

"We use the open-source version, which is available to use free of charge."

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

"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."

"There are different licenses available to be purchased, such as individual, premium, or enterprise."

More MongoDB Enterprise Advanced pricing and cost advice

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Top Industries

By visitors reading reviews

Construction Company

17%

Financial Services Firm

17%

Comms Service Provider

Healthcare Company

Financial Services Firm

15%

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

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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 15% of the time

Amazon EMR vs HPE Data Fabric

Compared 11% of the time

IBM Spectrum Computing 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 5% of the time

Redis vs MongoDB Enterprise Advanced

Compared 5% 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

September 2026

Download HPE Data Fabric product report

Buyer's Guide

MongoDB Enterprise Advanced

September 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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