IBM Analytics Engine vs. Sisense for Cloud Data Teams

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
Sisense for Cloud Data Teams
Score 6.5 out of 10
N/A
Sisense for Cloud Data Teams (formerly Periscope Data) is a data visualization tool that allows users to connect to their SQL databases to create sharable, interactive dashboards. In addition to SQL, its analytics integrate with R and Python, allowing users to prep datasets, perform analysis, and create their own visualizations. Sisense acquired Periscope Data in mid-2019.N/A
Pricing
IBM Analytics EngineSisense for Cloud Data Teams
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
IBM Analytics EngineSisense for Cloud Data Teams
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 EngineSisense for Cloud Data Teams
Considered Both Products
IBM Analytics Engine
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:

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 …
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 …
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 …
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 …
Chose IBM Analytics Engine
Hortonworks Data Platform, Apache Spark, Tableau Desktop and Tableau Online
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 …
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.
Sisense for Cloud Data Teams
Chose Sisense for Cloud Data Teams
RStudio requires custom code from programmers and the decision was made to move to software instead of software developers. Microsoft Power BI didn't have the right data subscription capabilities for our customers.
Chose Sisense for Cloud Data Teams
Google Analytics works well but it does not have all of the bells and whistles that Periscope Data offers. Google Analytics is best used in a Google environment but if you are using other tools and programs outside of the Google universe, then Periscope Data is a much better …
Chose Sisense for Cloud Data Teams
Periscope is far more robust than these two similar products. For a start up just getting going they are fine alternatives, but as your business scales Google Charts becomes a hassle to manage and Keap becomes too much of a generalized product. While your business increases it …
Chose Sisense for Cloud Data Teams
Periscope is by far the best we looked at - I was evaluating as a user, not the primary decision maker, and user interface and ease of use was the primary factor in my decision. It is very easy to navigate and manipulate, and has an overall very polished view.
Chose Sisense for Cloud Data Teams
Periscope's lightweight footprint and customizable SQL-based reports make it a better choice for us than Tableau or Microsoft BI. We deal with millions of rows of transactional data in a SQL Server data warehouse, so having seamless front-end integration makes reporting seamless.
Chose Sisense for Cloud Data Teams
We use Jira here at SDC, as well as Periscope. These programs are use together and they work in tandem to get the issues resolved.
Chose Sisense for Cloud Data Teams
Sharing of visualisations and rapid prototypen/building, ease of use. UX is 20x better.
Chose Sisense for Cloud Data Teams
LookML was able to simplify development of views involving window calculations, but slowed down the overall development cycle as minor SQL edits required heavy code reviews.

Tableau has great interactive options but has proved non-performant with our database mix (MySQL, …
Chose Sisense for Cloud Data Teams
This is currently our primary visualization tool. There is no real option to do any meaningful math on your data, and you only have access to a very, very limited subset of information you stream into the cache. Periscope far exceeds this tool with the ability to combine data …
Chose Sisense for Cloud Data Teams
Different in the sense that you need to be able to manipulate data with Periscope while you just need to understand how data is manipulated with Amplitude (Periscope = you need to master SQL vs Amplitude = you need to understand the logic of SQL). Periscope is a more powerful …
Chose Sisense for Cloud Data Teams
Periscope Data enables data wrangling and is more familiar to SQL-savvy people - which are mostly analysts. Writing query is not really tedious for them, so it is not a huge problem. Quick and nice response from Periscope support is really helpful for the users.
Chose Sisense for Cloud Data Teams
I have not utilized any other tools like Periscope so it's hard to say how it stacks up against its competition.
Features
IBM Analytics EngineSisense for Cloud Data Teams
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
IBM Analytics Engine
-
Ratings
Sisense for Cloud Data Teams
9.2
Ratings
9% above category average
Pixel Perfect reports00 Ratings8.80 Ratings
Customizable dashboards00 Ratings9.10 Ratings
Report Formatting Templates00 Ratings9.60 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
IBM Analytics Engine
-
Ratings
Sisense for Cloud Data Teams
8.8
Ratings
10% above category average
Drill-down analysis00 Ratings9.00 Ratings
Formatting capabilities00 Ratings9.20 Ratings
Integration with R or other statistical packages00 Ratings8.60 Ratings
Report sharing and collaboration00 Ratings8.60 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
IBM Analytics Engine
-
Ratings
Sisense for Cloud Data Teams
9.6
Ratings
13% above category average
Publish to Web00 Ratings9.60 Ratings
Publish to PDF00 Ratings9.60 Ratings
Report Versioning00 Ratings9.60 Ratings
Report Delivery Scheduling00 Ratings9.60 Ratings
Delivery to Remote Servers00 Ratings9.40 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
IBM Analytics Engine
-
Ratings
Sisense for Cloud Data Teams
8.7
Ratings
7% above category average
Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings8.30 Ratings
Location Analytics / Geographic Visualization00 Ratings8.80 Ratings
Predictive Analytics00 Ratings9.00 Ratings
Best Alternatives
IBM Analytics EngineSisense for Cloud Data Teams
Small Businesses

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Supermetrics
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Score 10.0 out of 10
Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
Supermetrics
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Score 10.0 out of 10
Enterprises
Apache Spark
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Score 9.2 out of 10
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Score 7.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
IBM Analytics EngineSisense for Cloud Data Teams
Likelihood to Recommend
9.5
(0 ratings)
8.4
(0 ratings)
Usability
-
(0 ratings)
9.0
(0 ratings)
Support Rating
-
(0 ratings)
8.0
(0 ratings)
User Testimonials
IBM Analytics EngineSisense for Cloud Data Teams
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
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Sisense for Cloud Data Teams is suited so well for our project that works with lots of data and needs some ways to share data internally or externally with our clients. It's very easy to pull out the data from the sense in best and in a suitable format and moreover a huge number of options are available there to represent the data. All features of this Sisense for cloud data teams software can be taken advantage of if you have a team who are well versed in data analytics, data management, and programming.
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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.
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  • Rapid deployment of polished T-SQL-based data visualization charts and dashboards. Periscope supports a variety of database technologies, and allows users to write custom queries to display data.
  • Included caching to reduce server load.
  • Outstanding customer service/support, with expert advice as needed.
  • Constant updates and new features.
  • Built-in SQL formatters take the pain out of manipulating date/time objects.
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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
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  • Some of the dashboards can be slow to load; especially when they have lots of features and widgets.
  • The software could be made a little easier for people that don't have a data or programming background.
  • It is pricey so not a great option for small companies or research/home projects.
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Usability
No answers on this topic
My company has had Periscope for various use cases in the past and I think that this program opens up complex data reports to non-technical people in a really accessible way (even though the learning curve is a big one). We are now integrating Sisense for Cloud Data Teams at a larger level both for internal data exploration and for customer facing dashboards and reports.
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Support Rating
No answers on this topic
The user interface is just amazing and it's really very easy to use and navigate, even for a newbie. Mostly it provides us the accurate data.
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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
Read full review
Periscope is far more robust than these two similar products. For a start up just getting going they are fine alternatives, but as your business scales Google Charts becomes a hassle to manage and Keap becomes too much of a generalized product. While your business increases it is generally best to get multiple specialized pieces of technology to help you maintain integrity in your data, and Periscope Data allows. Worth the money.
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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.
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  • Very positive - has allowed us to glean insights quickly and in real time.
  • Definitely helpful for evaluating performance of accounts and employees.
  • Versatile - we even use it with recruiting metrics, our software team uses it to test feature deployment.
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ScreenShots