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.
"Provides deep integration with other Azure resources."
"The way it organizes data into tables and dashboards is very helpful."
"The most valuable features are the IoT hub and the Blob storage."
"The integrations for this solution are easy to use and there is flexibility in integrating the tool with Azure Stream Analytics."
"I appreciate this solution because it leverages open-source technologies. It allows us to utilize the latest streaming solutions and it's easy to develop."
"I like the way the UI looks, and the real-time analytics service is aligned to this. That can be helpful if I have to use this on a production service."
"It's scalable as a cloud product."
"We use Azure Stream Analytics for simulation and internal activities."
"Databricks has helped us have a good presence in data."
"The ease of use and its accessibility are valuable."
"A very valuable feature is the data processing, and the solution is specifically good at using the Spark ecosystem."
"Its lightweight and fast processing are valuable."
"The load distribution capabilities are good, and you can perform data processing tasks very quickly."
"The main features of the solution are efficiency."
"It can send out large data amounts."
"Databricks provides a consistent interface for data engineers to work with data in a consistent language on a single integrated platform for ingesting, processing, and serving data to the end user."
"The solution's interface could be simpler to understand for non-technical people."
"Its features for event imports and architecture could be enhanced."
"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."
"The solution offers a free trial, however, it is too short."
"The only challenge was that the streaming analytics area in Azure Stream Analytics could not meet our company's expectations, making it a component where improvements are required."
"The UI should be a little bit better from a usability perspective."
"I would like to have a contact individual at Microsoft."
"One area that could use improvement is the handling of data validation. Currently, there is a review process, but sometimes the validation fails even before the job is executed. This results in wasted time as we have to rerun the job to identify the failure."
"Databricks may not be as easy to use as other tools, but if you simplify a tool too much, it won't have the flexibility to go in-depth. Databricks is completely in the programmer's hands. I prefer flexibility rather than simplicity."
"The integration and query capabilities can be improved."
"The Databricks cluster can be improved."
"The product needs samples and templates to help invite users to see results and understand what the product can do."
"Support for Microsoft technology and the compatibility with the .NET framework is somewhat missing."
"Anyone who doesn't know SQL may find the product difficult to work with."
"I would like to see more documentation in terms of how an end-user could use it, and users like me can easily try it and implement use cases."
"The interface of Databricks could be easier to use when compared to other solutions. It is not easy for non-data scientists. The user interface is important before we had to write code manually and as solutions move to "No code AI" it is critical that the interface is very good."
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 Data Science Studio, Microsoft Azure Machine Learning Studio and Tableau. 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.