Enables us to find anomalies and apply rules to the streaming data
Pros and Cons
"The ability to stream data and the windowing feature are valuable."
"Support for Microsoft technology and the compatibility with the .NET framework is somewhat missing."
What is our primary use case?
We use this solution for finding anomalies and applying the rules to the streaming data.
There are around 50 people using this solution in my organization, including data scientists.
What is most valuable?
The ability to stream data and the windowing feature are valuable. There are a number of targeted integration points, so that is a difference between Stream Analytics and Databricks. The integrations input or output are better in Databricks. It's accessible to use any of the Python or even Java. I can use the third party, deploy it, and use it.
What needs improvement?
Support for Microsoft technology and the compatibility with the .NET framework is somewhat missing. There should be reliability between these two. Databricks is based on open sources. If it's more synchronous between the Microsoft technology and the programming languages, it'll be better. Python has better languages, but compatibility would be a great help.
I would like to have better support for Microsoft technology and better language components.
With Azure or Cosmo DB, I can store other data links or time series data tables. That would be a great help for analytics in real time.
For how long have I used the solution?
I have been using Databricks for eight months.
What do I think about the scalability of the solution?
The scalability is fine. We had thousands of devices and were sending data infrequently, so that worked for us. If the amount increases, the windowing function and job schedule may not perform as expected.
How are customer service and support?
I would rate technical support 4 out of 5. We had some issues with setup, and they were finally solved but it was after following up a few times.
Which solution did I use previously and why did I switch?
Azure Stream Analytics is easy to use and easy to deploy. It's a little bit better. Databricks is still having some stability issues. Azure Stream Analytics has a few input and output sources, and it's scalable to all types of third party or interfaces.
How was the initial setup?
Setup was complex. There were some issues with setting up a database and installing the third party component on top of services. I would rate the setup 3 out of 5.
What about the implementation team?
Implementation was done in-house.
What's my experience with pricing, setup cost, and licensing?
The cost is around $600,000 for 50 users.
I would rate the price 2 out of 5.
What other advice do I have?
I would rate this solution 8 out of 10.
Disclosure: I am a real user, and this review is based on my own experience and opinions.