TrustRadius

HPE Data Fabric vs. Starburst Enterprise

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
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
Starburst Enterprise
Score 10.0 out of 10
N/A
Starburst Enterprise is a fully supported, production-tested and enterprise-grade distribution of open source Trino (formerly Presto® SQL). It aims to improve performance and security while making it easy to deploy, connect, and manage a Trino environment. Through connecting to any source of data – whether it’s located on-premise, in the cloud, or across a hybrid cloud environment – Starburst provides analytics tools to users while accessing data that lives anywhere.N/A
Pricing
HPE Data FabricStarburst Enterprise
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
HPE Data FabricStarburst Enterprise
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
Community Pulse
HPE Data FabricStarburst Enterprise
Considered Both Products
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 …
Starburst Enterprise
Kunal Sonalkar | TrustRadius Reviewer
Kunal Sonalkar
Supply Chain Data Analytics & Machine Learning
Chose Starburst Enterprise
Most of our systems were compatible with Starburst Presto. The dashboard which they provide was fairly intuitive and easy to use. The learning curve wasn't that much. Also, the parallel processing part was an additional feature that we didn't find in many competitive products. …
Best Alternatives
HPE Data FabricStarburst Enterprise
Small Businesses

No answers on this topic

No answers on this topic

Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
SAP HANA Cloud
SAP HANA Cloud
Score 8.9 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 7.1 out of 10
Perforce Delphix
Perforce Delphix
Score 9.9 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
HPE Data FabricStarburst Enterprise
Likelihood to Recommend
7.2
(0 ratings)
7.0
(0 ratings)
User Testimonials
HPE Data FabricStarburst Enterprise
Likelihood to Recommend
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
If you run a SQL query, Starburst Presto can help you track efficiently the status of SQL query. It can also track how many resources have been allocated for execution and what is the optimal way to run the query without hindrance. It also provides good information on worker nodes and how parallel threads are running together.
Kunal Sonalkar | TrustRadius Reviewer
Kunal Sonalkar
Supply Chain Data Analytics & Machine Learning
Read full review
Pros
  • 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
  • Query tracking.
  • Resource allocation.
  • Parallelizing query execution.
Kunal Sonalkar | TrustRadius Reviewer
Kunal Sonalkar
Supply Chain Data Analytics & Machine Learning
Read full review
Cons
  • 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
Read full review
  • Pricing
  • Platform can be made more intuitive.
  • Sometimes the platform hangs while aborting the query.
Kunal Sonalkar | TrustRadius Reviewer
Kunal Sonalkar
Supply Chain Data Analytics & Machine Learning
Read full review
Alternatives Considered
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
Most of our systems were compatible with Starburst Presto. The dashboard which they provide was fairly intuitive and easy to use. The learning curve wasn't that much. Also, the parallel processing part was an additional feature that we didn't find in many competitive products. The pricing was a little higher but it was worth the trade-off.
Kunal Sonalkar | TrustRadius Reviewer
Kunal Sonalkar
Supply Chain Data Analytics & Machine Learning
Read full review
Return on Investment
  • Less manual intervention for maintaining a cluster.
Verified User
Anonymous
Read full review
  • Neutral impact.
  • ROI on saving time for query execution.
  • Parallel processing saves time too.
Kunal Sonalkar | TrustRadius Reviewer
Kunal Sonalkar
Supply Chain Data Analytics & Machine Learning
Read full review
ScreenShots