HPE Ezmeral Data Fabric Reviews, Competitors and Pricing

it_user364158

Member of Technical Staff at a tech company with 51-200 employees

Jan 3, 2016

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We're now able to perform data analytics, IOE/IOT, and predictive analysis.

What is most valuable?

It has several valuable features, among them being the file system, High-Availability services, and NFS.

How has it helped my organization?

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

What needs improvement?

It'd like to see file system auditing, data encryption, and certification of other vendors' tools.

For how long have I used the solution?

I've used it for three years.

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What was my experience with deployment of the solution?

We've had no problems with deployment.

What do I think about the stability of the solution?

It hasn't be unstable for us.

What do I think about the scalability of the solution?

It's scaled for our needs.

How are customer service and support?

Customer Service:

I rate customer service a 7 out of 10.

Technical Support:

Technical support is a 7 out of 10.

Which solution did I use previously and why did I switch?

We were using another solution and switched because of MapR's highly available services, and the robust file system.

How was the initial setup?

The initial setup was straightforward.

What about the implementation team?

We implemented it in-house and it was pretty easy.

What was our ROI?

I can't tell what the ROI is at this moment.

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.

Disclosure: My company has a business relationship with this vendor other than being a customer: We are partners.

it_user347739

Director at a tech services company with 51-200 employees

Oct 6, 2016

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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.

Valuable Features:

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. Of course the same concept is available across any solution based on the Hadoop architecture, but MapR provides bundled services and UI driven configurations which would otherwise take a long time to understand and implement.

Improvements to My Organization:

We implemented this for our client where data from sensors was to be analyzed and sense to be made of this data. Sensor data is huge, and earlier there was no meaningful early warning raised against the discrepancies observed on Sensor’s Data. With the help of our Big Data solution, we have been consistently raising alerts as required.

Room for Improvement:

Installations and setups are still a bit cryptic and can be improved.
Skilled resource base in Big Data Tools is generally low and hence project costing is that much higher.

Other Advice:

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.

Disclosure: I am a real user, and this review is based on my own experience and opinions.

Buyer's Guide

HPE Ezmeral Data Fabric

November 2024

Free Report: HPE Ezmeral Data Fabric Reviews and More

Learn what your peers think about HPE Ezmeral Data Fabric. Get advice and tips from experienced pros sharing their opinions. Updated: November 2024.

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816,406 professionals have used our research since 2012.

it_user346962

IT Project Director at a tech company with 10,001+ employees

Nov 26, 2015

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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:

Customer service is good.

Technical Support:

Technical support is good.

Which solution did I use previously and why did I switch?

We switched because we were able to get better value for the money for support.

How was the initial setup?

Setup wasn't complex.

What about the implementation team?

We did it in-house. You should start small, and iterate often.

What was our ROI?

We don't have a quantifiable ROI yet. We still need to complete our proof of concept.

What other advice do I have?

I highly recommend MapR.

Disclosure: I am a real user, and this review is based on my own experience and opinions.

it_user364152

Senior Data Warehouse Specialist / Team Leader at a tech vendor with 10,001+ employees

Jan 3, 2016

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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 is most valuable?

MapR is one of three leading Hadoop distributions. The key differentiators I found the most valuable are:

Lack of namenode (no SPOF)
Performance – the base components are implemented in C
NFS functionality – copying to MapR FS is as easy as copying files to a directory

How has it helped my organization?

I haven't yet used it in production environments, but I've used it extensively in two proofs-of-concept.

What needs improvement?

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

What was my experience with deployment of the solution?

I've had no issues with deployment so far.

What do I think about the stability of the solution?

It's been stable so far.

What do I think about the scalability of the solution?

There have been no scalability issues so far.

How are customer service and technical support?

Customer Service:

I haven't yet had to use customer service.

Technical Support:

I haven't yet had to use technical service.

Which solution did I use previously and why did I switch?

I tested both Cloudera and Hortonworks, and I rate it similarly to Hortonworks and slightly higher than Cloudera.

How was the initial setup?

Initial setup is rather straightforward thanks to detailed documentation covering all the bases. More advanced installations required manual deployment to an extent, but this too is well-documented.

What about the implementation team?

I implemented it myself.

What was our ROI?

I haven't put it into production yet.

What other advice do I have?

I don't have any advice because the installation documentation is superb.

Disclosure: My company has a business relationship with this vendor other than being a customer: We have partnerships with all leading Hadoop vendors.