HPE Ezmeral Data Fabric Overview

HPE Ezmeral Data Fabric is the #6 ranked solution of our top Hadoop tools. It's rated 4.0 out of 5 stars, and is most commonly compared to Cloudera Distribution for Hadoop: HPE Ezmeral Data Fabric vs Cloudera Distribution for Hadoop

What is HPE Ezmeral Data Fabric?

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.

HPE Ezmeral Data Fabric is also known as MapR, MapR Data Platform.

HPE Ezmeral Data Fabric Buyer's Guide

Download the HPE Ezmeral Data Fabric Buyer's Guide including reviews and more. Updated: November 2020

HPE Ezmeral Data Fabric Customers

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

HPE Ezmeral Data Fabric Archived Reviews (More than two years old)

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MSegel
Founder at Chicago area Hadoop User Group (CHUG)
Real User
Mar 2, 2018
Because of their POSIX compliant file system, they can support read/write files over the WORM storage of their competitors

What is our primary use case?

As an independent consultant, I support multiple use cases depending on the client's need(s).
it_user693837
Technical Architect at a tech services company with 10,001+ employees
Consultant
Jun 29, 2017
​MapR-DB is a NoSQl datastore on top of MaprFS. The data can be updated and random data can be picked very fast.

What other advice do I have?

The biggest drawback is that it has vendor locking. It's proprietary in MapR distribution and extract cost. The positive side is that its storage is inherently within the MapR-FS and there is no region server overhead. Consider these aspects before making your decision.
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it_user347739
Director at a tech services company with 51-200 employees
Consultant
Oct 6, 2016
It provides bundled services and UI driven configurations which would otherwise take a long time to understand and implement, but the setups are still a bit cryptic and can be improved.

What other advice do I have?

Please make sure following answers are clearly known: * Define the Objectives, and what you are not currently able to achieve without Big Data Tools. * Why is the data big - because of velocity of data pouring in. th number of years of data, or a sudden increase in business operations * Define a sample use case / example of the expectations from Big Data analytics * Carry out a POC & review the objectives.
it_user364158
Member of Technical Staff at a tech company with 51-200 employees
Vendor
Jan 3, 2016
We're now able to perform data analytics, IOE/IOT, and predictive analysis.

What other advice do I have?

Make sure the third-party applications you are trying to implement with it are certified with this product. If not, please start discussing with the MapR team that they can start a partnership with the third-party application vendor.
it_user364152
Senior Data Warehouse Specialist / Team Leader at a tech vendor with 10,001+ employees
Vendor
Jan 3, 2016
It differentiates itself from other Hadoop distributions because of the lack of namenode, the base components are implemented in C, and the NFS functionality.

What other advice do I have?

I don't have any advice because the installation documentation is superb.
it_user346962
IT Project Director at a tech company with 10,001+ employees
MSP
Nov 26, 2015
It's allowed us to use Twitter as a data source to monitor the effectiveness of our marketing campaigns.

What is most valuable?

The most valuable features for us are-- MapR-DB Multi-tenancy

How has it helped my organization?

It's allowed us to use Twitter as a data source to monitor the effectiveness of our marketing campaigns.

What needs improvement?

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

For how long have I used the solution?

We've used it for six months.

What was my experience with deployment of the solution?

No issues encountered with deployment.

What do I think about the stability of the solution?

No issues encountered with stability.

What do I think about the scalability of the solution?

No issues encountered with scalability.

How are customer service and technical support?

Customer Service:…
it_user344895
Big Data Engineer at a tech services company with 51-200 employees
Consultant
Nov 24, 2015
It allows our Docker environment to write directly to HDFS and NoSQL on the MapR cluster without the need for other tools, but we had CLDB errors with M3 that made it seem a little unstable.

What other advice do I have?

In terms of Hadoop growing pains, there was some pain, compared to the M7 license which I found largely painless. However, it was nowhere near the amount of pain I had playing vanilla Hadoop. MapR is a great distribution, although I have limited experience with other distributors. I know that I have never come across the name node issue, and MapR even translates some posix calls to HDFS and abstracts away a lot of the complexity. It's enterprise ready, and comes with a host of features that really simplify some scenarios. For example, MapR NFS provides great flexibility when it comes to…
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