Gigasheet vs. IBM Analytics Engine

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Gigasheet
Score 0.0 out of 10
Small Businesses (1-50 employees)
Gigasheet is a big data spreadsheet that combines the ease of use of a spreadsheet, the power of a database, and the scale of the cloud, enabling anyone who can use a spreadsheet to analyze big data, without writing code. Instantly analyze big data sets. No database needed. Upload any huge data file, or import from popular cloud apps such as Google Drive, OneDrive, DropBox, and Box. Analyze multi-million row CSV files Query massive JSON data…
$79
per month per user
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
GigasheetIBM Analytics Engine
Editions & Modules
Premium
$79
per month per user
No answers on this topic
Offerings
Pricing Offerings
GigasheetIBM Analytics Engine
Free Trial
NoNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsEnterprise edition offers advanced customization for organizations, scale and support
More Pricing Information
Community Pulse
GigasheetIBM Analytics Engine
Best Alternatives
GigasheetIBM Analytics Engine
Small Businesses
Supermetrics
Supermetrics
Score 10.0 out of 10

No answers on this topic

Medium-sized Companies
Supermetrics
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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
GigasheetIBM Analytics Engine
Likelihood to Recommend
-
(0 ratings)
9.5
(0 ratings)
User Testimonials
GigasheetIBM 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
No answers on this topic
  • 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
No answers on this topic
  • 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
No answers on this topic
  • 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

Gigasheet Screenshots

Screenshot of Gigasheet - Big Data Cloud SpreadsheetScreenshot of Gigasheet no-code filtersScreenshot of Data cleanup tools