IBM BigInsights is an analytics and data visualization tool leveraging hadoop.
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Presto
Score 2.6 out of 10
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Presto is an open source SQL query engine designed to run queries on data stored in Hadoop or in traditional databases.
Teradata supported development of Presto followed the acquisition of Hadapt and Revelytix.
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
Simple stories & templates work nicely - like for our Insider program. Stories that include a lot of images may be challenging to create & have look appealing.
Linking, embedding links and adding images is easy enough.
Once you have become familiar with the interface, Presto becomes very quick & easy to use (but, you have to practice & repeat to know what you are doing - it is not as intuitive as one would hope).
Organizing & design is fairly simple with click & drag parameters.
Presto was not designed for large fact fact joins. This is by design as presto does not leverage disk and used memory for processing which in turn makes it fast.. However, this is a tradeoff..in an ideal world, people would like to use one system for all their use cases, and presto should get exhaustive by solving this problem.
Resource allocation is not similar to YARN and presto has a priority queue based query resource allocation..so a query that takes long takes longer...this might be alleviated by giving some more control back to the user to define priority/override.
UDF Support is not available in presto. You will have to write your own functions..while this is good for performance, it comes at a huge overhead of building exclusively for presto and not being interoperable with other systems like Hive, SparkSQL etc.
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
I think Presto is one of the best solutions out there today at the cutting edge for interactive query analysis. One of the challenges is presto is a niche tool for the interactive query use case and doesn't have the knobs and whistles as much as Spark. In the foreseeable future if they are able to make presto work without the need for Hive, solving all the gaps it could be game changing and can be a direct threat to spark
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.
