Azure Stream Analytics Competitors and Alternatives

The top Azure Stream Analytics competitors are
  • Apache Spark
  • Apache NiFi
  • Apache Storm
  • AWS Lambda
Read reviews of Azure Stream Analytics competitors and alternatives
it_user370506
Real User
Software Engineer at a consultancy with 1,001-5,000 employees
Jun 11 2017

What is most valuable?

We are a research institution and use NiFi for its easy Java extensibility, built-in provenance capturing, and... more»

How has it helped my organization?

We are replacing a custom built Java data ingestion system that over time had become difficult to maintain and was... more»

What needs improvement?

Most of our data is binary and we frequently must write our own processors. Also, there is no support for the stateful... more»

What's my experience with pricing, setup cost, and licensing?

It’s free!

Which other solutions did I evaluate?

We previously used custom code and switched to simplify maintenance and improve our functionality.

What other advice do I have?

Think about your data flows as the directed graphs between low-level processing modules, so you can re-use as much of... more»
Reviewer39213S
Real User
Chief Executive Officer at a tech services company with 51-200 employees
Jun 05 2018

What is most valuable?

The console is very good, the user experience works very well.

How has it helped my organization?

It has made things a lot easier in terms of restoring if we need to and just not having to worry about the small things.

What needs improvement?

I would like to see some better integration with other providers, like Cohesity, Druva, and others. I also think the Lambda interface could be better.

What other advice do I have?

My most important criteria when selecting a vendor are * user experience * support. I would rate AWS Lambda at a six out of 10 because it's not quite clear that it scales, but it... more»
ShivanshSrivastava
Real User
Sr. Software Engineer at a tech vendor with 1-10 employees
Oct 01 2017

What is most valuable?

The most valuable feature is the Fault Tolerance and easy binding with other processes like Machine Learning, graph analytics. The community is growing and hence executing ML in a... more»

How has it helped my organization?

Previously we were using Hadoop MapReduce to reduce the Google Ngrams (3TB), which took us approximately five days on our cluster. After using Spark, we were able to accomplish... more»

What needs improvement?

This product is already improving as the community is developing it rapidly. More ML based algorithms should be added to it, to make it algorithmic-rich for developers.

What other advice do I have?

This is a very good product for the big data analytics and integrates well with other parts like Machine Learning and graph analytics.

Sign Up with Email