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.
"The solution is very easy to use."
"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."
"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."
"We like that this solution can handle a wide variety and velocity of data engineering, either in batch mode or real-time."
"Databricks makes it really easy to use a number of technologies to do data analysis. In terms of languages, we can use Scala, Python, and SQL. Databricks enables you to run very large queries, at a massive scale, within really good timeframes."
"The initial setup is pretty easy."
"We have the ability to scale, collaborate and do machine learning."
"The simplicity of development is the most valuable feature."
"The stability is great and continues to get better and better."
"It ingegrates nicely with Office 365."
"In my experience the scalability is good. You are able to increase users and add more data."
"Easy to use and the visualization is valuable."
"It is easy to use. It has got a desktop where people can develop their own dashboards. Basically, we have figured out how to connect finance contracts and all programs for the government agency. So, they can see everything in a dashboard. So, it is very easy to use from a technical standpoint of view."
"There is continual improvement year-over-year."
"Many of my customers already use Microsoft products like Office 365, so I often propose Microsoft Power BI because it integrates well with all the standard Microsoft business tools. And it's the quickest tool to implement and start using daily."
"The visuals are great and make everything look very professional. We can change the look and feel or manipulate the data according to our requirements. It's extremely flexible."
"Databricks would benefit from enhanced metrics and tighter integration with Azure's diagnostics."
"Scalability is an area with certain shortcomings. The solution's scalability needs improvement."
"Databricks would have more collaborative features than it has. It should have some more customization for the jobs."
"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."
"Databricks is not geared towards the end-user, but rather it is for data engineers or data scientists."
"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."
"I would like more integration with SQL for using data in different workspaces."
"The Databricks cluster can be improved."
"The Microsoft BI interface should be simpler and more user-friendly. I find it very difficult to move between their data sources and their analytics section."
"Integrating it with the physics build model or the engineering model should be included."
"It is kept very current, and there is an update literally every month. However, the interface changes quite randomly with no documentation, which is difficult at the domain and architectural level where you're planning things and engaging the business. Things change frequently, and you wonder where has the button for the new report gone. They should provide better documentation on interface changes. It should be better optimized. It is supposed to be a data integration tool, but it is doing relatively simple queries. It has its limitations. For example, you can only pull a number of columns. So, there is room for optimization on its ability to integrate multiple data sources. The desktop tool is very memory-intensive, and again, this is not documented clearly. It requires a heavy CPU and memory use, and it causes your operating systems to become unstable. I would like to see the ability to create datasets within Power BI. Microsoft is promoting Azure as a cloud solution, but it is dependent upon a desktop component, which seems a little bit deceptive. Data set is the basic element that you report from, but it has to be created on the desktop and then published to the cloud. So, you're in the cloud, and you create a data structure or the data flow, but you can't report from that. You have to leave the cloud, go to your desktop, create the data set on your desktop, and publish it to the cloud. You go back to the cloud and create your report by using that published data set, which is very non-intuitive. If you go to the Microsoft Power BI community, this is a common complaint across the entire community."
"The integration with other solutions could be improved for reporting aspects."
"Our expectation is putting BI to work in real-time data collection systems in the maritime environment."
"The DAX in Microsoft BI is quite difficult."
"I believe there is room for improvement in terms of authentication and certain functionalities in Power BI. For instance, adjusting the width of columns is not easily done, as there is only an option to enable or disable automatic adjustment. This can be a significant drawback for clients who desire more flexibility."
"We would like it if they added more Python libraries in the Power BI service. For Power BI service right now, you can use Python, but it is limited to a few libraries or a few packages from Python."
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.