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 9.8% mindshare in the category. MongoDB is ranked #2 in ND , with an average rating of 8.4, and holds a 13.1% 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

2,389 Views
1,983 Comparison Views

100% willing to recommend

MongoDB Enterprise Advanced

Read 82 MongoDB Enterprise Advanced reviews

12,004 Views
5,762 Comparison Views

92% willing to recommend

HPE Data Fabric

MongoDB Enterprise Advanced

Comparison Buyer's Guide

Download the report

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: July 2026).

Buyer's Guide

Hadoop

July 2026

Download the complete report

Helped 908,800 peers since 2012

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 (7th), NoSQL Databases (2nd), Managed NoSQL Databases (6th)

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 9.8%, down 14.8% compared to last year.
MongoDB Enterprise Advanced, on the other hand, focuses on NoSQL Databases, holds 13.1% mindshare, down 15.2% since last year.

Hadoop Mindshare Distribution
Product	Mindshare (%)
HPE Data Fabric	9.8%
Cloudera Distribution for Hadoop	14.4%
Apache Spark	14.2%
Other	61.599999999999994%

Hadoop

NoSQL Databases Mindshare Distribution
Product	Mindshare (%)
MongoDB Enterprise Advanced	13.1%
Redis	8.3%
Cassandra	8.2%
Other	70.4%

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."

"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."

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

"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."

"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."

"I highly recommend MapR."

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

More HPE Data Fabric pros

"The feature I find most valuable is that it is easy to use and even a non-technical person will be able to understand it."

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

"It can handle a lot of files quickly."

"The integration capabilities of MongoDB are fine for the solutions that we use in our company."

"I like the document storage feature. It's pretty simple."

"MongoDB stores the JSON data, and it's easy for me to understand because I'm a JavaScript Developer."

"I found that MongoDB is most valuable for storing school-related queries. It's also user-friendly, and I found no difficulty accessing it. Setting it up is easy too."

"It is a stable solution. Stability-wise, I rate the solution a nine out of ten...Overall, MongoDB has helped manage and analyze attachment data."

More MongoDB Enterprise Advanced pros

Cons

"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."

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

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

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

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

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

"One weakness for MapR is the Kerberos support."

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

More HPE Data Fabric cons

"More stable indexes would be helpful in a future release. That's been an issue for some time. I don't know if it's been fixed now but we transitioned to it because we needed a search index to be able to search for things and if that goes or starts disappearing, we have to move away from that solution. I don't know if they fixed it, last time I had this issue was three years ago so they might have solved it."

"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."

"More stable indexes would be helpful in a future release. That's been an issue for some time."

"There is a need for improvement in MongoDB's customer support."

"We'd like information about client onboarding experience and success stories. It would help to have something to show to internal stakeholders."

"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."

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

"It could be more stable. It would be better if it were more user-friendly like Oracle, which is very easy."

More MongoDB Enterprise Advanced cons

Pricing and Cost Advice

"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."

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

"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."

"I only used the open-source version."

"It's a community edition, so we do not pay anything."

"MongoDB is an open-source product."

"The pricing is normal. Price-wise, the product is not too much expensive."

"We are using the Community Edition of MongoDB."

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

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

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

More MongoDB Enterprise Advanced pricing and cost advice

See which vendors are best for you

Use our free recommendation engine to learn which Hadoop solutions are best for your needs.

See recommendations

908,800 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Construction Company

18%

Financial Services Firm

17%

Healthcare Company

10%

Comms Service Provider

Financial Services Firm

15%

Manufacturing Company

Construction 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 16% 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 1% 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 5% 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

July 2026

Download HPE Data Fabric product report

Buyer's Guide

MongoDB Enterprise Advanced

July 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: July 2026.

DOWNLOAD NOW

908,800 professionals have used our research since 2012.

We monitor all Hadoop reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.