Apache Superset vs. IBM Analytics Engine

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Superset
Score 7.7 out of 10
N/A
Apache Superset is an open source data exploration and visualization platform, presented as lightweight but loaded with options that make it easy for users of all skill sets to explore and visualize their data.N/A
IBM Analytics Engine
Score 7.1 out of 10
N/A
IBM BigInsights is an analytics and data visualization tool leveraging hadoop.N/A
Pricing
Apache SupersetIBM Analytics Engine
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache SupersetIBM Analytics Engine
Free Trial
NoNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache SupersetIBM Analytics Engine
Best Alternatives
Apache SupersetIBM Analytics Engine
Small Businesses
Supermetrics
Supermetrics
Score 10.0 out of 10

No answers on this topic

Medium-sized Companies
Supermetrics
Supermetrics
Score 10.0 out of 10
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
Enterprises
Dataiku
Dataiku
Score 7.6 out of 10
Azure Data Lake Storage
Azure Data Lake Storage
Score 9.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache SupersetIBM Analytics Engine
Likelihood to Recommend
-
(0 ratings)
9.5
(0 ratings)
User Testimonials
Apache SupersetIBM Analytics Engine
Likelihood to Recommend
No answers on this topic
We are at present utilizing IBM Analytics Engine and it works incredible. Following are the things that I like the most about this product is:- - Simple to Utilize - Reasonable Cost - With only a couple seconds you can ready to fabricate and convey groups - you can without much of a stretch break down information through different applications
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Pros
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  • We are able to build and deploy clusters within minutes to simplify user experience and increase scalability and reliability.
  • We are able to scale and compute on-demand to handle newer workloads like machine learning.
  • We really like that we are able to access and administer the application via multiple interfaces.
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Cons
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  • I would like to see a more robust version of their online help
  • The speed of their business support is adequate, but I kind of expect more from such a powerhouse.
  • Problems with duration of cluster life
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Alternatives Considered
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  • I have been using Azure for my previous analysis, I had a difficult time in understanding the Analytics engine rather IBM provided step by step tutorial for setup.
  • Also turning off a machine was not an option in Azure for some of the services so I had to pay for the service whether I use it or not
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Return on Investment
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  • It has saved us quite a bit of time managing our catalog of clusters and keeping things organized.
  • Since we had a division we acquired running IBM Cloud, it was easy to get it running and try it out, but we found we prefer our Azure configuration better simply to keep our technology in alignment across corporate functions.
  • I definitely see some cost savings by separating out the storage and compute. It helps you start to put an appropriate price tag on certain instances of big data.
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ScreenShots