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 life cycle, report management and crash management features are great."
"Real-time analytics is the most valuable feature of this solution. I can send the collected data to Power BI in real time."
"It provides the capability to streamline multiple output components."
"The solution has a lot of functionality that can be pushed out to companies."
"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."
"The solution's most valuable feature is its ability to create a query using SQ."
"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."
"Databricks gives you the flexibility of using several programming languages independently or in combination to build models."
"It can send out large data amounts."
"We can scale the product."
"The initial setup is pretty easy."
"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."
"It's easy to increase performance as required."
"The simplicity of development is the most valuable feature."
"The setup is quite easy."
"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."
"Its features for event imports and architecture could be enhanced."
"The initial setup is complex."
"Sometimes when we connect Power BI, there is a delay or it throws up some errors, so we're not sure."
"I would like to have a contact individual at Microsoft."
"Early in the process, we had some issues with stability."
"If something goes wrong, it's very hard to investigate what caused it and why."
"Azure Stream Analytics could improve by having clearer metrics as to the scale, more metrics around the data set size that is flowing through it, and performance tuning recommendations."
"If I want to create a Databricks account, I need to have a prior cloud account such as an AWS account or an Azure account. Only then can I create a Databricks account on the cloud. However, if they can make it so that I can still try Databricks even if I don't have a cloud account on AWS and Azure, it would be great. That is, it would be nice if it were possible to create a pseudo account and be provided with a free trial. It is very essential to creating a workforce on Databricks. For example, students or corporate staff can then explore and learn Databricks."
"In the future, I would like to see Data Lake support. That is something that I'm looking forward to."
"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."
"Costs can quickly add up if you don't plan for it."
"It's not easy to use, and they need a better UI."
"Scalability is an area with certain shortcomings. The solution's scalability needs improvement."
"Databricks is an analytics platform. It should offer more data science. It should have more features for data scientists to work with."
"Support for Microsoft technology and the compatibility with the .NET framework is somewhat missing."
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.