In the first part of this series?comparing the competing analytics platform offerings from Microsoft Azure and Amazon AWS, we explored Azure Analytics Platform System and AWS Redshift. In this post, we will talk about comparing some of the other products in the ecosystem of analytics.

Microsoft Azure also offers Stream Analytics, that’s again a turnkey proprietary solution from Microsoft for cost effective real-time processing of events. With Stream Analytics, you can easily set up a variety of devices, sensors, web applications, social media and infrastructure to stream data and then perform real-time analytical computations on them. Stream Analytics is a powerful and effective platform for designing IoT solutions. It allows streaming millions of events per second and provides mission critical reliability. It also provides a familiar SQL based language support for rapid development using your existing SQL knowledge.

A competing offering from AWS is Kinesis Streams, however it is geared more towards application insights than devices and sensors. Stream Analytics actually seems to be competing against Apache Storm on Azure hosted as HDInsight. Both are offered as PaaS and support processing of virtually millions of events per second. A key difference, however, is that Stream Analytics deploy as monitoring jobs, while Storm on HDInsight deploys as clusters of monitoring jobs, hosting multiple stream jobs or other workloads. Another volumetric aspect to consider is that Stream Analytics is turnkey, whereas Storm on HDInsight allows lot of custom connectors and is extensible.

There are pricing considerations to make as well while making a choice between these platforms. In Stream Analytics, pricing is by the volume of data processed and number of streaming units, while in HDInsight, it is charged by the clusters irrespective of jobs that may or may not be running. This post?by Jeff Stokes details the differences.

(See also, Part 3?of this series)