Apache Spark vs HPE Ezmeral Data Fabric comparison

Cancel
You must select at least 2 products to compare!
Comparison Buyer's Guide
Executive Summary

We performed a comparison between Apache Spark and HPE Ezmeral Data Fabric based on real PeerSpot user reviews.

Find out in this report how the two Hadoop solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
To learn more, read our detailed Apache Spark vs. HPE Ezmeral Data Fabric Report (Updated: March 2024).
765,234 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The product’s most valuable feature is the SQL tool. It enables us to create a database and publish it.""The main feature that we find valuable is that it is very fast.""The memory processing engine is the solution's most valuable aspect. It processes everything extremely fast, and it's in the cluster itself. It acts as a memory engine and is very effective in processing data correctly.""The solution has been very stable.""I like that it can handle multiple tasks parallelly. I also like the automation feature. JavaScript also helps with the parallel streaming of the library.""The solution is very stable.""I appreciate everything about the solution, not just one or two specific features. The solution is highly stable. I rate it a perfect ten. The solution is highly scalable. I rate it a perfect ten. The initial setup was straightforward. I recommend using the solution. Overall, I rate the solution a perfect ten.""AI libraries are the most valuable. They provide extensibility and usability. Spark has a lot of connectors, which is a very important and useful feature for AI. You need to connect a lot of points for AI, and you have to get data from those systems. Connectors are very wide in Spark. With a Spark cluster, you can get fast results, especially for AI."

More Apache Spark Pros →

"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.""It is a stable solution...It is a scalable solution.""I like the administration part.""The model creation was very interesting, especially with the libraries provided by the platform.""HPE Ezmeral Data Fabric can be accessed from any namespace globally as you would access it from a machine using an NFS."

More HPE Ezmeral Data Fabric Pros →

Cons
"Apache Spark provides very good performance The tuning phase is still tricky.""The migration of data between different versions could be improved.""We are building our own queries on Spark, and it can be improved in terms of query handling.""One limitation is that not all machine learning libraries and models support it.""I would like to see integration with data science platforms to optimize the processing capability for these tasks.""In data analysis, you need to take real-time data from different data sources. You need to process this in a subsecond, do the transformation in a subsecond, and all that.""The management tools could use improvement. Some of the debugging tools need some work as well. They need to be more descriptive.""The solution needs to optimize shuffling between workers."

More Apache Spark 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.""The deployment could be faster. I want more support for the data lake in the next release.""Having the ability to extend the services provided by the platform to an API architecture, a micro-services architecture, could be very helpful.""The product is not user-friendly.""HPE Ezmeral Data Fabric is not compatible with third-party tools."

More HPE Ezmeral Data Fabric Cons →

Pricing and Cost Advice
  • "Since we are using the Apache Spark version, not the data bricks version, it is an Apache license version, the support and resolution of the bug are actually late or delayed. The Apache license is free."
  • "Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera."
  • "We are using the free version of the solution."
  • "Apache Spark is not too cheap. You have to pay for hardware and Cloudera licenses. Of course, there is a solution with open source without Cloudera."
  • "Apache Spark is an expensive solution."
  • "Spark is an open-source solution, so there are no licensing costs."
  • "On the cloud model can be expensive as it requires substantial resources for implementation, covering on-premises hardware, memory, and licensing."
  • "It is an open-source solution, it is free of charge."
  • More Apache Spark 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."
  • "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."
  • More HPE Ezmeral Data Fabric Pricing and Cost Advice →

    report
    Use our free recommendation engine to learn which Hadoop solutions are best for your needs.
    765,234 professionals have used our research since 2012.
    Questions from the Community
    Top Answer:The product’s most valuable features are lazy evaluation and workload distribution.
    Top Answer:They provide an open-source license for the on-premise version. However, we have to pay for the cloud version including data centers and virtual machines.
    Top Answer:They could improve the issues related to programming language for the platform.
    Top Answer:It is a stable solution...It is a scalable solution.
    Top Answer:There are some drawbacks in HPE Ezmeral Data Fabric when it comes to the interoperability part. HPE Ezmeral Data Fabric is not compatible with third-party tools. For example, HPE Ezmeral Data Fabric… more »
    Top Answer:The main purpose of HPE Ezmeral Data Fabric for me is that it acts as a database. In my company, we store our data with the help of HPE Ezmeral Data Fabric. It is possible to use Spark engine with HPE… more »
    Ranking
    2nd
    out of 22 in Hadoop
    Views
    2,468
    Comparisons
    1,915
    Reviews
    20
    Average Words per Review
    387
    Rating
    8.6
    5th
    out of 22 in Hadoop
    Views
    1,711
    Comparisons
    1,097
    Reviews
    4
    Average Words per Review
    550
    Rating
    7.8
    Comparisons
    Also Known As
    MapR, MapR Data Platform
    Learn More
    Overview

    Spark provides programmers with an application programming interface centered on a data structure called the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. It was developed in response to limitations in the MapReduce cluster computing paradigm, which forces a particular linear dataflowstructure on distributed programs: MapReduce programs read input data from disk, map a function across the data, reduce the results of the map, and store reduction results on disk. Spark's RDDs function as a working set for distributed programs that offers a (deliberately) restricted form of distributed shared memory

    Forward-leaning companies win market share because they leverage data more effectively than their competitors. Unlock the potential of your data assets with HPE Ezmeral Data Fabric (formerly MapR Data Platform). Empower your data science, analytics, and business teams by simplifying data management on a globally distributed scale. All with enterprise-grade reliability, security, and performance.

    Sample Customers
    NASA JPL, UC Berkeley AMPLab, Amazon, eBay, Yahoo!, UC Santa Cruz, TripAdvisor, Taboola, Agile Lab, Art.com, Baidu, Alibaba Taobao, EURECOM, Hitachi Solutions
    Valence Health, Goodgame Studios, Pico, Terbium Labs, sovrn, Harte Hanks, Quantium, Razorsight, Novartis, Experian, Dentsu ix, Pontis Transitions, DataSong, Return Path, RAPP, HP
    Top Industries
    REVIEWERS
    Computer Software Company30%
    Financial Services Firm15%
    University9%
    Marketing Services Firm6%
    VISITORS READING REVIEWS
    Financial Services Firm25%
    Computer Software Company13%
    Manufacturing Company7%
    Comms Service Provider6%
    VISITORS READING REVIEWS
    Computer Software Company18%
    Financial Services Firm17%
    Comms Service Provider7%
    Government7%
    Company Size
    REVIEWERS
    Small Business40%
    Midsize Enterprise19%
    Large Enterprise40%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise12%
    Large Enterprise71%
    REVIEWERS
    Small Business36%
    Large Enterprise64%
    VISITORS READING REVIEWS
    Small Business24%
    Midsize Enterprise12%
    Large Enterprise65%
    Buyer's Guide
    Apache Spark vs. HPE Ezmeral Data Fabric
    March 2024
    Find out what your peers are saying about Apache Spark vs. HPE Ezmeral Data Fabric and other solutions. Updated: March 2024.
    765,234 professionals have used our research since 2012.

    Apache Spark is ranked 2nd in Hadoop with 58 reviews while HPE Ezmeral Data Fabric is ranked 5th in Hadoop with 12 reviews. Apache Spark is rated 8.4, while HPE Ezmeral Data Fabric is rated 8.0. The top reviewer of Apache Spark writes "Reliable, able to expand, and handle large amounts of data well". On the other hand, the top reviewer of HPE Ezmeral Data Fabric writes "It's flexible and easily accessible across multiple locations, but the upgrade process is complicated". Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and Cloudera Distribution for Hadoop, whereas HPE Ezmeral Data Fabric is most compared with Cloudera Distribution for Hadoop, Amazon EMR, MongoDB, IBM Spectrum Computing and BlueData. See our Apache Spark vs. HPE Ezmeral Data Fabric report.

    See our list of best Hadoop vendors.

    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.