We performed a comparison between Azure Stream Analytics and Databricks based on our users’ reviews in five categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: Databricks is the winner in this comparison. It is stable and powerful with good machine learning features. Azure Stream Analytics does come out on top in the pricing category, however.
"We use Azure Stream Analytics for simulation and internal activities."
"The solution has a lot of functionality that can be pushed out to companies."
"The solution's most valuable feature is its ability to create a query using SQ."
"I like all the connected ecosystems of Microsoft, it is really good with other BI tools that are easy to connect."
"The integrations for this solution are easy to use and there is flexibility in integrating the tool with Azure Stream Analytics."
"It's scalable as a cloud product."
"The most valuable features of Azure Stream Analytics are the ease of provisioning and the interface is not terribly complex."
"Technical support is pretty helpful."
"Databricks is hosted on the cloud. It is very easy to collaborate with other team members who are working on it. It is production-ready code, and scheduling the jobs is easy."
"Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great."
"The most valuable feature of Databricks is the integration with Microsoft Azure."
"The Delta Lake data type has been the most useful part of this solution. Delta Lake is an opensource data type and it was implemented and invented by Databricks."
"The most valuable feature of Databricks is the notebook, data factory, and ease of use."
"The solution's features are fantastic and include interactive clusters that perform at top speed when compared to other solutions."
"Automation with Databricks is very easy when using the API."
"The time travel feature is the solution's most valuable aspect."
"The UI should be a little bit better from a usability perspective."
"The initial setup is complex."
"The solution's interface could be simpler to understand for non-technical people."
"Sometimes when we connect Power BI, there is a delay or it throws up some errors, so we're not sure."
"The solution could be improved by providing better graphics and including support for UI and UX testing."
"The collection and analysis of historical data could be better."
"We would like to have centralized platform altogether since we have different kind of options for data ingestion. Sometimes it gets difficult to manage different platforms."
"It is not complex, but it requires some development skills. When the data is sent from Azure Stream Analytics to Power BI, I don't have the access to modify the data. I can't customize or edit the data or do some queries. All queries need to be done in the Azure Stream Analytics."
"It would be great if Databricks could integrate all the cloud platforms."
"Databricks doesn't offer the use of Python scripts by itself and is not connected to GitHub repositories or anything similar. This is something that is missing. if they could integrate with Git tools it would be an advantage."
"The integration and query capabilities can be improved."
"I would love an integration in my desktop IDE. For now, I have to code on their webpage."
"Databricks is not geared towards the end-user, but rather it is for data engineers or data scientists."
"The data visualization for this solution could be improved. They have started to roll out a data visualization tool inside Databricks but it is in the early stages. It's not comparable to a solution like Power BI, Luca, or Tableau."
"The product should incorporate more learning aspects. It needs to have a free trial version that the team can practice."
"I believe that this product could be improved by becoming more user-friendly."
Azure Stream Analytics is ranked 3rd in Streaming Analytics with 22 reviews while Databricks is ranked 2nd in Streaming Analytics with 78 reviews. Azure Stream Analytics is rated 8.2, while Databricks is rated 8.2. The top reviewer of Azure Stream Analytics writes "Easy to set up and user-friendly, but could be priced better". On the other hand, the top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". Azure Stream Analytics is most compared with Amazon Kinesis, Amazon MSK, Apache Flink, Apache Spark and Apache Spark Streaming, whereas Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Dremio and Google Cloud Dataflow. See our Azure Stream Analytics vs. Databricks report.
See our list of best Streaming Analytics vendors.
We monitor all Streaming Analytics reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.