TrustRadius

Element Unify vs. HPE Data Fabric

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Element Unify
Score 0.0 out of 10
N/A
Element powers digitally-enabled operations for the Industrial Enterprise. Tackling a critical gap in Industrial IoT –– the fact that 95% of data across the Industrial Enterprise is unusable because it’s fragmented and disconnected –– Element Unify breaks through the data silos by bringing IT and OT data and teams together on a single solution. With Element Unify, IT and OT teams can collaboratively make data-driven operational and business decisions around contextualized metadata.N/A
HPE Data Fabric
Score 9.4 out of 10
N/A
HPE Data Fabric (formerly MapR, acquired by HPE in 2019) is a software-defined datastore and file system that simplifies data management and analytics by unifying data across core, edge, and multicloud sources into a single platform.N/A
Pricing
Element UnifyHPE Data Fabric
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Element UnifyHPE Data Fabric
Free Trial
YesNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
Community Pulse
Element UnifyHPE Data Fabric
Considered Both Products
Element Unify

No answer on this topic

HPE Data Fabric
CK
Chavez Kattick
Software Engineer
Chose HPE Data Fabric
I don't believe there is as much support for MapR yet compared to other more widely known products.
Verified User
Anonymous
Chose HPE Data Fabric
Hortonworks and Cloudera are both sort of hacky. We have to do a lot of extra steps to automate those two. MapR has far fewer issues and doesn't force you into a once size fits all deployment scenario. There are multiple ways to deploy and some are more amenable to automation, …
Verified User
Anonymous
Chose HPE Data Fabric
When we were shopping, Mapr had the momentum, high availability even on Hadoop 1.x, an improved file system and better a central control system. Now it looks like the situation has changed a lot.
Verified User
Anonymous
Chose HPE Data Fabric
We supported all three Hadoop vendors with our Hadoop RDBMS product. Here's how I see the commercial Hadoop distribution world. If you need raw performance and don't mind proprietary technology, go with MapR. If you care about the most pure open source, go with Hortonworks. If …
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Element UnifyHPE Data Fabric
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No answers on this topic

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User Ratings
Element UnifyHPE Data Fabric
Likelihood to Recommend
-
(0 ratings)
7.2
(0 ratings)
User Testimonials
Element UnifyHPE Data Fabric
Likelihood to Recommend
No answers on this topic
If you need Hadoop and just need raw speed for I/O and have a Hadoop savvy group of engineers who don't need/like web UIs, then MapR is a great fit for you. If you are new to Hadoop or have DevOps folks that are not Hadoop gurus, choosing MapR as your Hadoop vendor will have a steeper learning curve as you will need to do more training and build more admin consoles for them.
Verified User
Anonymous
Read full review
Pros
No answers on this topic
  • MapR allows easy integration with HBase and MapR DB.
  • Easy trial server setup for product testing.
  • Excellent training program to help new users get up-to-date with MapR and related products.
Chavez Kattick | TrustRadius Reviewer
Chavez Kattick
Software Engineer
Read full review
Cons
No answers on this topic
  • I think MapR's main problem is name recognition. Hortonworks and Cloudera both are big names in the industry, but their deployment mechanisms are a little more difficult to use, especially when trying to fully automate it's deployment.
  • Documentation could always be better. But really, if that's your main weakness, it's everybody's weakness.
Verified User
Anonymous
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Alternatives Considered
No answers on this topic
Hortonworks and Cloudera are both sort of hacky. We have to do a lot of extra steps to automate those two. MapR has far fewer issues and doesn't force you into a once size fits all deployment scenario. There are multiple ways to deploy and some are more amenable to automation, MapR just has that in spades
Verified User
Anonymous
Read full review
Return on Investment
No answers on this topic
  • Less manual intervention for maintaining a cluster.
Verified User
Anonymous
Read full review
ScreenShots

Element Unify Screenshots

Screenshot of Capture data relationships in a semantic data model realizing flexibility and ability to keep model in sync with underlying assets.Screenshot of Easily publish graph models to AWS IoT TwinMaker in the form of components, documents and parameters.Screenshot of Several custom connectors available for Microsoft Azure Digital Twins.