Azure HDInsight vs. IBM Analytics for Apache Spark

Well suited: A tiny-mid sized company with no immediate plans of growing the volume of their data processing, that can afford long response times from support. Also it helps if you are not prone to put your hands on Linux and Spark configuration. In fact, it can make things go really faster if you also work with the bundle-in Jupyter. And, if you need to perform some diagnostics and / or administrative tasks, that's full of tools to find an understand the Root Cause. Ideal for non experts. Less appropriate: Big Data company, intense on demand cluster creation, mission critical, costs reduction, latest versions of libraries required, sophisticate customizations required.

Incentivized

• Data is presented without interfering others (IT or other dept).
• Data is managed properly and is available for retrievable any time.
• Legacy use of CD/DVD and Pendrive are not required.

Incentivized

• The only problem I have come across is when loading large volumes of data I sometimes get an error message, I assume this means something is corrupt from within. I would love a way for this to be resolved without having to start over.

Incentivized

Azure HDInsight is usable on the top of Azure Data Lake and gives us the benefit of analyzing large scale data workload in Hadoop. Usability and support from Microsoft are outstanding.

Incentivized

Inexpert, isolated teams... not good for support an excessively complex platform. Lots of weeks or months for a complex problem troubleshoot. Many time lost stuck on MindTree, before the case was finally escalated with Microsoft!

Incentivized

At this time I have not used any other similar products... I am open to it but Azure HDInsight and its components really work well for our organization.

Incentivized

• ROI is of course there, as no legacy software for data presentation.
• No manual intervention for data retrieval.
• Data is available anywhere as requested.

Incentivized