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IBM Analytics Engine vs. Shiny

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM Analytics Engine
Score 7.1 out of 10
N/A
IBM BigInsights is an analytics and data visualization tool leveraging hadoop.N/A
Shiny
Score 8.0 out of 10
N/A
Shiny allows users to create data visualization apps, and is designed to be easy to write with. These apps let users interact with data and analyses with R or Python.N/A
Pricing
IBM Analytics EngineShiny
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
IBM Analytics EngineShiny
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
Community Pulse
IBM Analytics EngineShiny
Considered Both Products
IBM Analytics Engine
Verified User
Anonymous
Chose IBM Analytics Engine
We have tried the following solutions in the past and I must say they can't compare to IBM Analytics Engine:

Ejaz Hussain | TrustRadius Reviewer
Ejaz Hussain
Senior Analyst
Chose IBM Analytics Engine
Our data analytics team happened to try IBM Analytics just to get acquainted with it & it turned out that this tool fits our business requirement better than the one which we were using in terms of the features along with the level of support that they provide. so, choosing the …
Verified User
Anonymous
Chose IBM Analytics Engine
IBM Analytics is a great tool and a welcome addition to your overall IBM strategy. I think in cases of tools like this, you either go with what your platform works best with or you go completely different with a 3rd party, like Snowflake. We are an Azure shop and just happened …
Verified User
Anonymous
Chose IBM Analytics Engine
We initially wanted to go with Google BigQuery, mainly for the name recognition. However, the pricing and support structure led us to seek alternatives, which pointed us to IBM. Apache Spark was also in the running, but here IBM's domination in the industry made the choice a …
Verified User
Anonymous
Chose IBM Analytics Engine
We did an evaluation of Google Analytics and Microsoft Azure Stream Analytics in comparison to the IBM Analytics Engine product. We choose the product offering from IBM because we felt that for our company, this product offered a more complete and comprehensive package to …
Verified User
Anonymous
Chose IBM Analytics Engine
Hortonworks Data Platform, Apache Spark, Tableau Desktop and Tableau Online
Prasanna Nattuthurai | TrustRadius Reviewer
Prasanna Nattuthurai
Graduate Assistant
Chose IBM Analytics Engine
  • 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 …
Verified User
Anonymous
Chose IBM Analytics Engine
Our professor has worked with IBM And many major tech companies. He’d recommend us which tools to use. And comparing to Azure, IBM is more convenient to use.
Shiny
Verified User
Anonymous
Chose Shiny
Whilst dashboarding may be comparable with some of the other products we evaluated. Nothing compared to the analytical capabilities on offer with Shiny. An added advantage was that we had colleagues knowledgeable in R which meant bringing in Shiny and getting to grips with it …
Kenton Woods | TrustRadius Reviewer
Kenton Woods
Research Assistant
Chose Shiny
Shiny is much cheaper to use than Tableau Desktop and Microsoft Power BI. It's not as fancy, and maybe not as effective, but you save lots of money by using Shiny over the previously listed alternatives. The graphs and charts you can make in Shiny are very good for …
Verified User
Anonymous
Chose Shiny
Both Tableau and Power BI are easier to learn and allow you to develop dashboards in a faster and more intuitive way, but both have limitations in what you can do with them and if you want to do something more specific it is always more complicated. RStudio is much more …
Verified User
Anonymous
Chose Shiny
- Faster response working with a large amount of data.
- R Studio connection and flexibility.
- Scenarios modelling.
VK
Varun Kumar
Data Science and Analytics Lead
Chose Shiny
Shiny can be a good tool in academic but its not upto standard of TMT industry but could possibly be useful in life science industry (which is where its more prevalent usually), its good as its mostly free (not including cost of servers and compute). I would rank its …
Verified User
Anonymous
Chose Shiny
Shiny allows easy and fast development of a product into production whereas Jupyter Notebook can be broken really easily by a user. The idea of having a specific server that works with that model is very practical and it's a good advantage.
In the contrary, the quantity of …
Best Alternatives
IBM Analytics EngineShiny
Small Businesses

No answers on this topic

Supermetrics
Supermetrics
Score 9.7 out of 10
Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
Supermetrics
Supermetrics
Score 9.7 out of 10
Enterprises
Apache Spark
Apache Spark
Score 8.9 out of 10
IBM Analytics Engine
IBM Analytics Engine
Score 7.1 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
IBM Analytics EngineShiny
Likelihood to Recommend
9.5
(0 ratings)
8.0
(0 ratings)
User Testimonials
IBM Analytics EngineShiny
Likelihood to Recommend
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
Read full review
Shiny is very good for developing dashboards or web applications with specific functionalities. But it is not so easy to use to develop from scratch, it is always better to use another tool to have a general idea of ​​what is expected of a dashboard and then develop the most specific functionalities in Shiny. It is much more flexible than other tools and that is why I consider it to be better for most cases, only that it is more complex to develop or has a longer learning curve.
Verified User
Anonymous
Read full review
Pros
  • 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
Read full review
  • Data tables are appealing to look at.
  • Enables us to create trend indexes in an effective way.
  • Easy to integrate with the rest of my R syntax.
Kenton Woods | TrustRadius Reviewer
Kenton Woods
Research Assistant
Read full review
Cons
  • 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
Read full review
  • Shiny can be really time consuming to create visuals.
  • It needs excellent knowledge of R programming and coding skillset.
  • It still has a limited set of options to choose from.
VK
Varun Kumar
Data Science and Analytics Lead
Read full review
Alternatives Considered
  • 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
Read full review
Whilst dashboarding may be comparable with some of the other products we evaluated. Nothing compared to the analytical capabilities on offer with Shiny. An added advantage was that we had colleagues knowledgeable in R which meant bringing in Shiny and getting to grips with it was a lot more seamless and welcomed by the end users.
Verified User
Anonymous
Read full review
Return on Investment
  • 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
Read full review
  • We saw a good involvement to researchers when showing their models in shiny.
  • We can have a quicker review from the user when the model is in production.
  • False positives can be found easily and they help the retraining of the model.
Verified User
Anonymous
Read full review
ScreenShots