We performed a comparison between Databricks and Tableau based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."In the manufacturing industry, Databricks can be beneficial to use because of machine learning. It is useful for tasks, such as product analysis or predictive maintenance."
"It's great technology."
"The capacity of use of the different types of coding is valuable. Databricks also has good performance because it is running in spark extra storage, meaning the performance and the capacity use different kinds of codes."
"Databricks' Lakehouse architecture has been most useful for us. The data governance has been absolutely efficient in between other kinds of solutions."
"We have the ability to scale, collaborate and do machine learning."
"I like cloud scalability and data access for any type of user."
"When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"The solution is very simple and stable."
"The most valuable feature is the geographic data analysis."
"The initial setup is quick and easy and you don't need special outside assistance to set everything up."
"The best part about Tableau is the visualization."
"Easy for beginners to use"
"The most valuable features are the visualizations, the way they show the combination charts."
"The solution has a lot of customization when comparing to Microsoft BI."
"It has made the reporting stage simple and enabled us to focus mainly on the ETL part"
"This solution has transformed us from an Excel reporting environment to one of visual exploration."
"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."
"The connectivity with various BI tools could be improved, specifically the performance and real time integration."
"Instead of relying on a massive instance, the solution should offer micro partition levels. They're working on it, however, they need to implement it to help the solution run more effectively."
"Databricks has a lack of debuggers, and it would be good to see more components."
"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."
"In the next release, I would like to see more optimization features."
"Would be helpful to have additional licensing options."
"The solution has some scalability and integration limitations when consolidating legacy systems."
"They need to improve the icons and the filters, because they look too old, resembling Excel from 1997."
"Its integration with Microsoft products such as Teams should be improved."
"It is not so great when it comes to data exchange/integration, data mining, etc."
"I would like them to include the Italian language, as I can see there are other foreign language in the product."
"The development part should be better. We are putting a lot of effort in during development, so if we face any struggles, we have to find workaround solutions on the internet."
"There are more than a powerful tool in the market, such as Microsoft BI."
"The user experience for less savvy or non-technical people (from my experience)."
"Users would like to be able to export an Excel file when they see a table or something like that. That's not an out-of-the-box feature for Tableau."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while Tableau is ranked 2nd in BI (Business Intelligence) Tools with 293 reviews. Databricks is rated 8.2, while Tableau is rated 8.4. 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 Tableau writes "Provides fast data access with in-memory extracts, makes it easy to create visualizations, and saves time". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Microsoft Azure Machine Learning Studio and Microsoft Power BI, whereas Tableau is most compared with Microsoft Power BI, Amazon QuickSight, Domo, SAS Visual Analytics and SAP Analytics Cloud. See our Databricks vs. Tableau report.
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