We performed a comparison between Databricks and Microsoft BI 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 robust, high performing, and received good feedback for its speed.
"I like that Databricks is a unified platform that lets you do streaming and batch processing in the same place. You can do analytics, too. They have added something called Databricks SQL Analytics, allowing users to connect to the data lake to perform analytics. Databricks also will enable you to share your data securely. It integrates with your reporting system as well."
"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."
"Databricks' most valuable features are the workspace and notebooks. Its integration, interface, and documentation are also good."
"Databricks' Lakehouse architecture has been most useful for us. The data governance has been absolutely efficient in between other kinds of solutions."
"The simplicity of development is the most valuable feature."
"The solution is built from Spark and has integration with MLflow, which is important for our use case."
"It can send out large data amounts."
"A very valuable feature is the data processing, and the solution is specifically good at using the Spark ecosystem."
"The most valuable feature of Microsoft Power BI is the drill-through feature that takes you to a details page the users want to see."
"Power BI stands out because it provides considerable flexibility in creating reports, dashboards, and various types of analytics to meet those dynamic requirements. It is lightweight and easy to use with good support."
"It is very well integrated with other Microsoft products, including PowerApps and Excel, as well as Access, so it fits well into our workflow."
"Power BI is a complete ecosystem. It has an integrated ETL tool and good connectivity with applications such as Office 365 and SQL. There are also solutions for RPA, such as Microsoft Power Automate and Microsoft Power Apps. Power BI now has integration with Power Query, which has an AI feature for text analytics. Text analytics is a very good feature. This feature is also there in Tableau, but I like it in Power BI because you can write something like, "What is the total sale in the Eastern region?", and it will give you the answer. For example, when you have different types of user opinions, you just run one algorithm and you will have the output that provides the number of positive and negative responses. You can even have a dashboard with positive remarks. This feature has been introduced recently. Power BI supports the DAX and Power Query M languages. These languages are making Power BI very strong in data analytics, and you can do many types of analysis."
"Microsoft BI is scalable."
"Like all Microsoft products, it is very easy to set up initially."
"The solution is very intuitive, you do not need to have too much programming knowledge to use it. Advanced Excel users can use it very easily."
"My favorite feature is the power query editor, where it can do the data transformations."
"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."
"There could be more support for automated machine learning in the database. I would like to see more ways to do analysis so that the reporting is more understandable."
"Costs can quickly add up if you don't plan for it."
"I would love an integration in my desktop IDE. For now, I have to code on their webpage."
"Support for Microsoft technology and the compatibility with the .NET framework is somewhat missing."
"Databricks would have more collaborative features than it has. It should have some more customization for the jobs."
"The integration of data could be a bit better."
"Databricks could improve in some of its functionality."
"The biggest thing with Microsoft right now is better support. There should be more timely support. We can do 90% of it ourselves by the same token. When we're into the 10%, we do not get timely support via Microsoft's support team."
"The solution could improve by simplifying the user interface and adding integration or compatibility with APA."
"There are some limitations in Power BI; you have to work in the Power BI base. However, if you want something not out-of-the-box and you want something custom, you have to do a lot of work."
"When there are large amounts of data being processed there are additional tools needed to handle it."
"I cannot comment on the stability as we haven't yet used it for a big project."
"Areas for improvement would be the construction of reports and the dashboard budget."
"Real-time updating needs improvement."
"Most clients have MacBooks. Therefore, they use Tableau as Power BI Desktop is not available for the MacBook right now."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while Microsoft Power BI is ranked 1st in BI (Business Intelligence) Tools with 297 reviews. Databricks is rated 8.2, while Microsoft Power BI is rated 8.0. The top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". On the other hand, the top reviewer of Microsoft Power BI writes "A complete ecosystem with an builtin ETL tool, good integrations with python and R, and support of DAX and Power Query (M languages)". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Microsoft Azure Machine Learning Studio and Alteryx, whereas Microsoft Power BI is most compared with Tableau, Amazon QuickSight, KNIME, Domo and MicroStrategy.
We monitor all Data Science Platforms 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.