DataStax Enterprise vs HPE Data Fabric comparison

Why PeerSpot?

The compared IBM and Hewlett Packard Enterprise solutions aren't in the same category. IBM is ranked #12 in ND , with an average rating of 8.6, and holds a 3.7% mindshare in the category. Hewlett Packard Enterprise is ranked #4 in H , and holds a 9.3% mindshare. Additionally, 100% of IBM users are willing to recommend the solution, compared to 100% of Hewlett Packard Enterprise users who would recommend it.

DataStax Enterprise

Read 7 DataStax Enterprise reviews

2,024 Views
1,133 Comparison Views

100% willing to recommend

HPE Data Fabric

Read 12 HPE Data Fabric reviews

2,682 Views
2,226 Comparison Views

100% willing to recommend

DataStax Enterprise

HPE Data Fabric

Comparison Buyer's Guide

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Executive Summary

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

Find out what your peers are saying about Microsoft, MongoDB, Redis and others in NoSQL Databases.

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NoSQL Databases

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

DataStax Enterprise

Average Rating

8.6

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

NoSQL Databases (12th), Vector Databases (13th)

HPE Data Fabric

Average Rating

8.0

Reviews Sentiment

6.1

Number of Reviews

Ranking in other categories

Hadoop (4th)

Mindshare comparison

DataStax Enterprise and HPE Data Fabric aren’t in the same category and serve different purposes. DataStax Enterprise is designed for NoSQL Databases and holds a mindshare of 3.7%, up 1.3% compared to last year.
HPE Data Fabric, on the other hand, focuses on Hadoop, holds 9.3% mindshare, down 14.4% since last year.

NoSQL Databases Mindshare Distribution
Product	Mindshare (%)
DataStax Enterprise	3.7%
MongoDB Enterprise Advanced	11.5%
Cassandra	8.7%
Other	76.1%

NoSQL Databases

Hadoop Mindshare Distribution
Product	Mindshare (%)
HPE Data Fabric	9.3%
Cloudera Distribution for Hadoop	14.7%
Apache Spark	14.3%
Other	61.7%

Hadoop

Featured Reviews

Pooja Singh

Devops Specialist at a tech vendor with 10,001+ employees

Reliable backup and recovery has protected critical telecom customer data in daily operations

When I was taking the backup with a data volume of 15 to 20 GB, the full backup running for the first time did not provide metrics to understand what percent of progress had been made. We had to read the logs, but we did not see any percentage in those logs. This is an improvement item for DataStax Enterprise to provide metrics, a bar, or a percentage so we can grasp how much data has been backed up or restored. There are no graphs available to make us aware of how long the process will take to complete, which is a drawback I noticed during backup and restore. In addition, I notice a huge time lag during restoration because each node takes a lot of time to be added to the pool and to the cluster node, one by one. The entire time the production is down presents a concerning situation. There should be an alternative for restoring where data can be provided to live traffic so it does not impact customers in the case of a disaster.

Read full review

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

Quotes from Members

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

Pros

"DataStax Enterprise has positively impacted my organization as we are now an e-commerce website that has never faced downtime, which helps our business to boom and significantly enhances our customer experience."

"DataStax Enterprise has positively impacted my organization by helping us handle large amounts of data more easily and quickly, improving our system speed, and making our application more reliable."

"I can share specific outcomes resulting from using DataStax Enterprise as we have been seeing an uptick in user adoption, since the introduction of this, our users have jumped from around 20,000 to 50,000."

"DataStax Enterprise is highly scalable, very reliable, and easy to manage and troubleshoot, helping us host a lot of complicated data efficiently because it is an upgraded version of relational database systems based on Cassandra, with a backup and recovery process that is also pretty smooth."

"The customer support for DataStax Enterprise is amazing, as any requests I have raised receive prompt responses, often within minutes, and the support engineers are knowledgeable and helpful."

"I can share specific outcomes or metrics that show this positive impact, such as improvements in performance of about 60% and a reduction in downtime of about 40 to 45%, which is very great."

"Some of the positive outcomes I see are that system stability improved a lot, there is no single point of failure, so downtime is reduced significantly, and the system stays up even when we face issues in a node."

"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."

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

"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."

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

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

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

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

More HPE Data Fabric pros

Cons

"If not keeping current with updates, updating from an older major version to a newer major version can be a bit complicated and time-consuming, but DataStax Enterprise support will help us with this."

"There is still room for improvement and DataStax Enterprise can definitely improve their UI."

"I believe that DataStax Enterprise could be improved by working more on making the OpsCenter user interface more user-friendly, particularly regarding the fonts and overall UI."

"The user interface of DataStax Enterprise can be simpler and easier to use, especially for new users, and I think it should be improved in that area."

"In addition, I notice a huge time lag during restoration because each node takes a lot of time to be added to the pool and to the cluster node, one by one."

"I believe DataStax Enterprise could be easier in areas such as operational complexity, especially for those coming from a traditional relational database background."

"My experience with pricing, setup cost, and licensing is that I feel the cost is a bit expensive compared to the open-source implementation of Cassandra, and the initial cluster setup is complex."

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

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

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

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

"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."

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

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

More HPE Data Fabric cons

Pricing and Cost Advice

Information not available

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

15%

Outsourcing Company

11%

Manufacturing Company

Construction Company

17%

Financial Services Firm

16%

Comms Service Provider

10%

Healthcare Company

10%

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	4
Large Enterprise	7

Questions from the Community

What is your experience regarding pricing and costs for DataStax Enterprise?

I was not involved in the licensing for DataStax Enterprise, which is managed by a different team, but I understand it operates on a core-based licensing model, which is standard. The licensing tea...

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What needs improvement with DataStax Enterprise?

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What is your primary use case for DataStax Enterprise?

DataStax Enterprise is currently deployed in production at Amdocs where we provide service to the AT&T account. To store customer data, we manage all customer usage information. Our company is ...

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Comparisons

Cassandra vs DataStax Enterprise

Compared 14% of the time

Cloudera Distribution for Hadoop vs DataStax Enterprise

Compared 10% of the time

Neo4j Graph Database vs DataStax Enterprise

Compared 9% of the time

Pinecone vs DataStax Enterprise

Compared 9% of the time

ClickHouse vs DataStax Enterprise

Compared 6% of the time

More DataStax Enterprise Competitors

Cloudera Distribution for Hadoop vs HPE Data Fabric

Compared 16% 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

More HPE Data Fabric Competitors

Product Reports

Buyer's Guide

DataStax Enterprise

October 2026

Download DataStax Enterprise product report

Buyer's Guide

HPE Data Fabric

October 2026

Download HPE Data Fabric product report

Also Known As

No data available

MapR, MapR Data Platform

Overview

DataStax Enterprise offers a high-performance, scalable database solution designed for modern data requirements, supporting a wide array of use cases that demand real-time analytics and robust security.

Focusing on delivering powerful distributed databases, DataStax Enterprise integrates the open-source foundation of Apache Cassandra, delivering enhanced features for enterprises. It supports mission-critical applications at scale, providing real-time query capabilities and fault tolerance. Designed with high availability and operational efficiency, it supports complex data models and simplifies management with advanced tools for monitoring and repair.

What are the standout features of DataStax Enterprise?

Advanced Security: Provides comprehensive data protection with encryption and identity management.
Graph Database Support: Allows complex data relationships to be easily modeled and queried.
Search Integration: Facilitates full-text search capabilities combined with Cassandra's strengths.
Analytics: Offers integrated analytics with Apache Spark for real-time data processing.
Multi-Cloud Support: Ensures easy deployment across different cloud environments without vendor lock-in.

What benefits should reviews highlight?

Scalability: Seamlessly expands to accommodate growing data volumes and user demands.
Performance: Maintains high-speed data processing even at massive scales.
Resilience: Provides high availability to ensure business continuity.
Cost Efficiency: Enables optimization of infrastructure investments with flexible deployments.

In industries such as finance, telecommunications, and retail, DataStax Enterprise is implemented to handle immense data workloads, often leveraging its capabilities for fraud detection, personalized customer experiences, and real-time decision-making. Its deployment in these sectors highlights its adaptability and performance in demanding environments.

IBM

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

Sample Customers

ING, Netflix, UBS, eBay, Constant Contact, Aeris, Arise, ClearCapital, Dyn, Engine, Noble Group, Pantheon, Target

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

Find out what your peers are saying about Microsoft, MongoDB, Redis and others in NoSQL Databases. Updated: October 2026.

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