IBM Analytics Engine vs. Vizlib

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

Incentivized

We produce a lot of graphs, so it's good to have the controls available from Vizlib

Incentivized

• 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.

Incentivized

• Their sales demo was excellent and compelling
• Their concept of write back to source data from within Qlik is very powerful and needed.

• 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

Incentivized

• Performance on large data sets
• Training courses
• Nonprofit pricing

We haven't had any troubles

Incentivized

Vizlib support is awesome! We have quick turnaround times and regular updates when we open cases. It’s so good we often ask them Qlik Sense questions, rather than going to Qlik support

• 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

Incentivized

I selected Vizlib based on several positive Qlik community forum comments. It would seem that they had a different use case than we did

• 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.

Incentivized

• Faster time to dashboards and reports
• Improved communication to donors of our key mission metrics
• Better support than from Qlik