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.
"The most valuable features of Azure Stream Analytics are the ease of provisioning and the interface is not terribly complex."
"Provides deep integration with other Azure resources."
"We find the query editor feature of this solution extremely valuable for our business."
"The solution's most valuable feature is its ability to create a query using SQ."
"It's a product that can scale."
"The solution has a lot of functionality that can be pushed out to companies."
"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."
"The way it organizes data into tables and dashboards is very helpful."
"When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"There are good features for turning off clusters."
"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."
"This solution offers a lake house data concept that we have found exciting. We are able to have a large amount of data in a data lake and can manage all relational activities."
"I work in the data science field and I found Databricks to be very useful."
"Databricks covers end-to-end data analytics workflow in one platform, this is the best feature of the solution."
"Databricks' Lakehouse architecture has been most useful for us. The data governance has been absolutely efficient in between other kinds of solutions."
"It's great technology."
"The solution could be improved by providing better graphics and including support for UI and UX testing."
"The solution’s customer support could be improved."
"The solution doesn't handle large data packets very efficiently, which could be improved upon."
"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."
"Early in the process, we had some issues with stability."
"The collection and analysis of historical data could be better."
"Sometimes when we connect Power BI, there is a delay or it throws up some errors, so we're not sure."
"The solution's interface could be simpler to understand for non-technical people."
"There is room for improvement in visualization."
"It would be nice to have more guidance on integrations with ETLs and other data quality tools."
"The pricing of Databricks could be cheaper."
"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 Databricks cluster can be improved."
"There should be better integration with other platforms."
"It would be better if it were faster. It can be slow, and it can be super fast for big data. But for small data, sometimes there is a sub-second response, which can be considered slow. In the next release, I would like to have automatic creation of APIs because they don't have it at the moment, and I spend a lot of time building them."
"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."
Azure Stream Analytics is ranked 4th in Streaming Analytics with 22 reviews while Databricks is ranked 1st 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.