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."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."
"Its lightweight and fast processing are valuable."
"The solution is built from Spark and has integration with MLflow, which is important for our use case."
"The most valuable feature is the ability to use SQL directly with Databricks."
"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."
"Ability to work collaboratively without having to worry about the infrastructure."
"A very valuable feature is the data processing, and the solution is specifically good at using the Spark ecosystem."
"Databricks covers end-to-end data analytics workflow in one platform, this is the best feature of the solution."
"The solution is configurable and flexible. We can customize the dashboards and configure the interface the way that we want. The data can be manipulated and arranged in different ways, such as columns."
"Tableau is highly scalable. Now that they've introduced Hyper, you can create an extract of more than 5 million rows in minutes and then do your analysis."
"This solution has improved insights into quantitative data."
"It has a shallow learning curve and so you can go to market very, very, very quickly."
"The Web Editing capabilities allow us to grant end users enough capabilities for them to do self-serve discovery without the added cost of needing to get everyone desktop licenses."
"Tableau's visualization features let you present information insights quickly and practically. So it's something which I prefer with Tableau. In terms of reporting, I have to point out the sheer quality and function of the Tableau server, but the first impression is that it's a great visualization tool."
"The solution makes for very productive and really informative decision making. It can lead the whole business and build a strategy across whole working departments."
"From the data science point of view, we use it for model building purposes. For example, if we are using it for a bank and we want to understand how much loan the bank can provide, we can use visualization to show the educational qualification, salary, gender, and city of a customer, and by using this information, we can arrive at the loan amount that this person is eligible for. I can also use it to view all prospective customers, so essentially, this is going to help me in model building as well as in understanding and segmenting customers and doing forecasting and predictive analytics. We use model widgets, and we can create thousands of visualizations, such as motion charts and bubble charts. We can also create animated versions of the graphs and view the data from multiple dimensions. These are the features that we typically use and like."
"The stability of the clusters or the instances of Databricks would be better if it was a much more stable environment. We've had issues with crashes."
"This solution only supports queries in SQL and Python, which is a bit limiting."
"If I want to create a Databricks account, I need to have a prior cloud account such as an AWS account or an Azure account. Only then can I create a Databricks account on the cloud. However, if they can make it so that I can still try Databricks even if I don't have a cloud account on AWS and Azure, it would be great. That is, it would be nice if it were possible to create a pseudo account and be provided with a free trial. It is very essential to creating a workforce on Databricks. For example, students or corporate staff can then explore and learn Databricks."
"The initial setup is difficult."
"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."
"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."
"There is room for improvement in visualization."
"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."
"With performance tuning, it generates a pretty complex query when it is not required."
"I am not a frequent user of this solution, so I am not sure what they've been doing recently. The last time when I used it, I had to use other tools with it for data extraction and cleansing. Its price should also be improved. It is more expensive than Power BI. In terms of training, there is generally better online training for Power BI, but I am not sure of that. It would be helpful to know from where to access its training."
"The performance could be better."
"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."
"To be the best in the market, Tableau has to improve its user interface and also look into developing implementing the best machine learning algorithms."
"Tableau is an end-to-end analytics platform, and it is doing a pretty good job in terms of connecting to the data and analyzing it. It can, however, do better in terms of data management and the ETL features, which are not on the advanced analytics or machine learning side. Tableau Prep is where users would want to see more advancements. They can improve Tableau Prep, which is an analytic platform tool for data cleansing. People who work with data spend most of their time curating the data. Cleaning up the data and getting it ready for analysis is what takes the most time. If Tableau can invest more time in improving the Tableau Prep platform, it would be great. Previously, Tableau didn't have the functionality for writing to a database. So, you couldn't really alter the database tables and write to your database, but they fixed that in one of the very recent releases. However, it isn't really advanced and should be improved."
"Maybe the price could be a bit cheaper, especially if you're a personal developer that uses Tableau just to explore smaller data sets and you're not a company or something like that."
"The solution needs to improve its integration capabilities."
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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