TrustRadius

IBM Analytics Engine vs. SeekWell, from ThoughtSpot

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
SeekWell, from ThoughtSpot
Score 10.0 out of 10
N/A
Seekwell, now from ThoughtSpot (acquired April, 2021) is presented as a data analytics and visualization tool for analysts and product managers who are looking to share SQL across their team, write SQL faster, and automate reports in Google Sheets. Seekwell connects SQL databases to Google Sheets and Slack and automatically updates reports and surfaces relevant past queries.
$50
per month
Pricing
IBM Analytics EngineSeekWell, from ThoughtSpot
Editions & Modules
No answers on this topic
Starter
$50.00
per month
Pro
$150.00
per month
Team
$300.00
per month
Company
$500.00
per month
Enterprise
Contact Sales
Offerings
Pricing Offerings
IBM Analytics EngineSeekWell, from ThoughtSpot
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
Community Pulse
IBM Analytics EngineSeekWell, from ThoughtSpot
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.
SeekWell, from ThoughtSpot

No answer on this topic

Best Alternatives
IBM Analytics EngineSeekWell, from ThoughtSpot
Small Businesses

No answers on this topic

Supermetrics
Supermetrics
Score 10.0 out of 10
Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
Supermetrics
Supermetrics
Score 10.0 out of 10
Enterprises
Apache Spark
Apache Spark
Score 9.2 out of 10
Dataiku
Dataiku
Score 7.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
IBM Analytics EngineSeekWell, from ThoughtSpot
Likelihood to Recommend
9.5
(0 ratings)
-
(0 ratings)
User Testimonials
IBM Analytics EngineSeekWell, from ThoughtSpot
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
No answers on this topic
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
No answers on this topic
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
No answers on this topic
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
No answers on this topic
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
No answers on this topic
ScreenShots