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 easy to increase performance as required."
"Automation with Databricks is very easy when using the API."
"The technical support is good."
"One of the features provides nice interactive clusters, or compute instances that you don't really need to manage often."
"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."
"Databricks' most valuable features are the workspace and notebooks. Its integration, interface, and documentation are also good."
"Databricks helps crunch petabytes of data in a very short period of time."
"I believe one of the most valuable features of the solution is trend analysis."
"The most valuable features of the solution are the permission management and the user management."
"The most valuable feature is the drag and drop, then the simplicity to build dashboards which allows us to provide more usable data to our customers."
"Tableau Prep tool for data preparation is a most valuable tool."
"From my perspective, it enables clients to better understand our data and make better decisions based on that information."
"It is very easy to implement and to use."
"Provides a very good sound analysis quotient."
"Technical support has been responsive."
"The product cannot be integrated with a popular coding IDE."
"When I used the support, I had communication problems because of the language barrier with the agent. The accent was difficult to understand."
"Some of the error messages that we receive are too vague, saying things like "unknown exception", and these should be improved to make it easier for developers to debug problems."
"The integration of data could be a bit better."
"Databricks may not be as easy to use as other tools, but if you simplify a tool too much, it won't have the flexibility to go in-depth. Databricks is completely in the programmer's hands. I prefer flexibility rather than simplicity."
"Implementation of Databricks is still very code heavy."
"The solution could be improved by integrating it with data packets. Right now, the load tables provide a function, like team collaboration. Still, it's unclear as to if there's a function to create different branches and/or more branches. Our team had used data packets before, however, I feel it's difficult to integrate the current with the previous data packets."
"Costs can quickly add up if you don't plan for it."
"Its price is a concern. It is more expensive than Power BI. The other thing that I never liked about Tableau is its ability to handle large sets of data. To present the data in the dashboards, we have to stage it up exactly like it is going to come into the dashboard. We use another tool called Alteryx that does that for us. So, we manipulate the data, get it staged, and then push it into Tableau. Tableau is terrible at handling large data sets, and we knew right away that we couldn't use Tableau to do data manipulation."
"Its documentation can be improved so that a user can get a good hands-on experience. Tableau is well documented, and on their website, there are a lot of tutorials that are available for free. I started my learning process through those tutorials, but there are certain loopholes in those tutorials, which only got filled through a couple of good YouTube channels that talk about Tableau. YouTube helped me a lot. So, the documentation could be better, I understand that it is evolving day by day, and with more usage, there would be more such documentation."
"The charts need to be improved. The drawings and the visualization need to be more accurate."
"Its integration with Microsoft products such as Teams should be improved."
"The process of embedding the dashboards on external portals and websites could be improved."
"We would like a report model, because currently there is no schema that we can create in the tool."
"Tableau's automatic insight could be improved. It has some predefined capabilities to understand the data, but I think they need more. Customers need more insight automatically from data—they don't want to discover them, they want to get the forecast automatically. The data preparation should also be improved because it's not easy. Tableau tries to focus on the business side, but the backend side has not improved much. They also have an ETS solution, but it's limited."
"An advanced type of visualization is a bit tricky to create. It has something called a Calculated field, and that sometimes gets a bit difficult to use when you want to create an advanced type of visualization."
Databricks is ranked 1st in Data Science Platforms with 47 reviews while Tableau is ranked 2nd in BI (Business Intelligence) Tools with 18 reviews. Databricks is rated 8.2, while Tableau is rated 8.4. The top reviewer of Databricks writes "Ahead of the competition in building data ecosystems, but needs to improve ease-of-use". 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, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio and Google Cloud Dataflow, whereas Tableau is most compared with Microsoft Power BI, Amazon QuickSight, Domo, SAS Visual Analytics and Qlik Sense. See our Databricks vs. Tableau report.
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