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.
"Its lightweight and fast processing are valuable."
"A very valuable feature is the data processing, and the solution is specifically good at using the Spark ecosystem."
"There are good features for turning off clusters."
"The most valuable feature of Databricks is the integration with Microsoft Azure."
"The setup was straightforward."
"The solution is very simple and stable."
"Databricks is a unified solution that we can use for streaming. It is supporting open source languages, which are cloud-agnostic. When I do database coding if any other tool has a similar language pack to Excel or SQL, I can use the same knowledge, limiting the need to learn new things. It supports a lot of Python libraries where I can use some very easily."
"Specifically for data science and data analytics purposes, it can handle large amounts of data in less time. I can compare it with Teradata. If a job takes five hours with Teradata databases, Databricks can complete it in around three to three and a half hours."
"MS SQL & SQL Server Analysis Services."
"I like all the tools in Microsoft BI because they all have different purposes. There are a lot of people using Microsoft BI, and everybody is using it. The users have adapted well to the technology."
"Its visualizations and dashboards are most valuable. Power BI is great in terms of visualizations and dashboards. The reports that we previously had were not very nice in terms of visualization. It also provides the ability to play with the data."
"The most valuable features of Microsoft BI are its intuitiveness and ease to use."
"You can learn a lot of things quickly using resources like ChatGPT or Microsoft's own solutions, which are very helpful within the Microsoft ecosystem."
"The good part of it is that you can do whatever you want with it when it comes to building BI. In terms of languages, it supports Python, and it also natively supports R."
"Everything that's in M Query and DAX is the heart of Power BI because with these tools you can make up for a lot of other missing features."
"Microsoft BI is scalable."
"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."
"I would like to see the integration between Databricks and MLflow improved. It is quite hard to train multiple models in parallel in the distributed fashions. You hit rate limits on the clients very fast."
"Databricks is an analytics platform. It should offer more data science. It should have more features for data scientists to work with."
"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."
"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."
"Databricks requires writing code in Python or SQL, so if you're a good programmer then you can use Databricks."
"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."
"The solution could be improved by adding a feature that would make it more user-friendly for our team. The feature is simple, but it would be useful. Currently, our team is more familiar with the language R, but Databricks requires the use of Jupyter Notebooks which primarily supports Python. We have tried using RStudio, but it is not a fully integrated solution. To fully utilize Databricks, we have to use the Jupyter interface. One feature that would make it easier for our team to adopt the Jupyter interface would be the ability to select a specific variable or line of code and execute it within a cell. This feature is available in other Jupyter Notebooks outside of Databricks and in our own IDE, but it is not currently available within Databricks. If this feature were added, it would make the transition to using Databricks much smoother for our team."
"You do need to do some hard coding for certain things in Microsoft BI."
"The product doesn't support unstructured data. It doesn't support video, streaming, and strings of files."
"The only concern I have faced with Microsoft BI is the time it takes to find out an issue and rectify it."
"Microsoft BI’s integration and visualization could be improved."
"Its performance and stability can be improved. It takes time to load, and sometimes, it also breaks down for the whole region. Its usability could also be better, and it could also have more connections with different data sources."
"The formatting template could be improved."
"The integration with other solutions could be improved for reporting aspects."
"I would like for the next release to have better desktop performance, especially for big databases. Additionally, I would like to have more integrations with programs like Salesforce in order to get more live data coming in."
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.
