TrustRadius

Graph Commons vs. IBM Analytics Engine

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Graph Commons
Score 0.0 out of 10
N/A
Graph Commons is a self-service collaborative platform for mapping, analyzing, and sharing data-networks. With its interactive network visualization and analysis tools online, Graph Commons aims to empower people and organizations to harness the intelligence of their networks, by transforming their data into interactive maps and untangling complex relations that impact them. Graph Commons offers an empty canvas to get started mapping a network, whether it's a social network, a supply…
$0
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
Graph CommonsIBM Analytics Engine
Editions & Modules
Starter
$0
Professional
$15
per month
Organization
$180
per month Starting from 1 Admin + 3 Explorer seats
No answers on this topic
Offerings
Pricing Offerings
Graph CommonsIBM 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
Graph CommonsIBM Analytics Engine
Best Alternatives
Graph CommonsIBM 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
Graph CommonsIBM Analytics Engine
Likelihood to Recommend
-
(0 ratings)
9.5
(0 ratings)
User Testimonials
Graph CommonsIBM 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
Verified User
Anonymous
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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.
Verified User
Anonymous
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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
Verified User
Anonymous
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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
Prasanna Nattuthurai | TrustRadius Reviewer
Prasanna Nattuthurai
Graduate Assistant
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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.
Verified User
Anonymous
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ScreenShots

Graph Commons Screenshots

Screenshot of Network of 🦄 Unicorns and 💰InvestorsScreenshot of Analyzing data with visual methods helps to gain insights about complexity. This makes sense of a complex issue by mapping actors and relations across networked organizations, or when investigating intermingled interactions of an ecosystem, or when curating a large archive.Screenshot of While exploring interactive network maps on Graph Commons, users can deep dive into the data.Screenshot of Centrality and clustering are the core network analysis metrics all available in Graph Commons.Screenshot of Two nodes in a network are considered "similar" if they share many common neighbors. When opening the similarity analysis dialogue, it presents options for selecting node types and their particular relationship types to generate a similarity analysis.