Datameer vs HPE Ezmeral Data Fabric comparison

The compared Datameer and Hewlett Packard Enterprise solutions aren't in the same category. Datameer is ranked #4 in BoH , and holds a 7.8% mindshare in the category. Hewlett Packard Enterprise is ranked #4 in H , with an average rating of 8.0, and holds a 14.8% mindshare. Additionally, 40% of Datameer users are willing to recommend the solution, compared to 100% of Hewlett Packard Enterprise users who would recommend it.

Datameer

Read 4 Datameer reviews

142 Views
36 Comparison Views

40% willing to recommend

HPE Ezmeral Data Fabric

Read 12 HPE Ezmeral Data Fabric reviews

1,172 Views
984 Comparison Views

100% willing to recommend

Datameer

HPE Ezmeral Data Fabric

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

Datameer

Average Rating

7.2

Number of Reviews

Ranking in other categories

BI on Hadoop (4th)

HPE Ezmeral Data Fabric

Average Rating

8.0

Reviews Sentiment

6.1

Number of Reviews

Ranking in other categories

Hadoop (4th)

Mindshare comparison

Datameer and HPE Ezmeral Data Fabric aren’t in the same category and serve different purposes. Datameer is designed for BI on Hadoop and holds a mindshare of 7.8%, down 23.5% compared to last year.
HPE Ezmeral Data Fabric, on the other hand, focuses on Hadoop, holds 14.8% mindshare, up 13.2% since last year.

BI on Hadoop

Hadoop

Featured Reviews

it_user357459

Hadoop Developer at a tech services company with 10,001+ employees

It helps to onboard and enrich data quickly as it does not involve writing scripts or queries, but the transformation functions can be more mature.

The most valuable feature are the data transformation functions in the workbook It helps to onboard and enrich data quickly as it does not involve writing scripts or queries. Maintenance is easy. We would like to have more inbuilt connections to different types of sources. The transformation…

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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.

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Top Industries

By visitors reading reviews

No data available

Financial Services Firm

19%

Computer Software Company

12%

Comms Service Provider

11%

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

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What do you like most about HPE Ezmeral Data Fabric?

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

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What needs improvement with HPE Ezmeral Data Fabric?

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 Fabri...

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What is your primary use case for HPE Ezmeral Data Fabric?

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 ...

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Comparisons

Databricks vs Datameer

Compared 100% of the time

More Datameer Competitors

Cloudera Distribution for Hadoop vs HPE Ezmeral Data Fabric

Compared 49% of the time

Cloudera Data Platform vs HPE Ezmeral Data Fabric

Compared 11% of the time

Apache Spark vs HPE Ezmeral Data Fabric

Compared 10% of the time

Amazon EMR vs HPE Ezmeral Data Fabric

Compared 8% of the time

IBM Analytics Engine vs HPE Ezmeral Data Fabric

Compared 8% of the time

More HPE Ezmeral Data Fabric Competitors

Product Reports

No data available

Buyer's Guide

HPE Ezmeral Data Fabric

August 2025

Download HPE Ezmeral Data Fabric product report

Also Known As

No data available

MapR, MapR Data Platform

Overview

Datameer specializes in analysis of large volumes of data for business users of Apache Hadoop. The company's product, Datameer Analytics Solution (DAS), is a business integration platform for Hadoop and includes data source integration, an analytics engine with a spreadsheet interface designed for business users with over 200 analytic functions and visualization including reports, charts and dashboards. DAS is available for major Hadoop distributions including Apache, Cloudera, EMC Greenplum HD, IBM BigInsights, MapR, Yahoo! and Amazon.

Datameer

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.

Hewlett Packard Enterprise

Sample Customers

Trustev, DetroitCrime Commission, Sears, Visa, citi, vivint, workday, Kabam, USA Olympic Team, CDW, BT, at&t, Bank of America, NetApp., expresso

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

We monitor all BI on 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.