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29,064 views|24,210 comparisons
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44,552 views|35,986 comparisons
Top Review
Find out what your peers are saying about Databricks vs. Tableau and other solutions. Updated: January 2021.
542,721 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
"We are completely satisfied with the ease of connecting to different sources of data or pocket files in the search""Automation with Databricks is very easy when using the API.""Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great.""The most valuable aspect of the solution is its notebook. It's quite convenient to use, both terms of the research and the development and also the final deployment, I can just declare the spark jobs by the load tables. It's quite convenient.""I work in the data science field and I found Databricks to be very useful.""The time travel feature is the solution's most valuable aspect.""I haven't heard about any major stability issues. At this time I feel like it's stable.""Imageflow is a visual tool that helps make it easier for business people to understand complex workflows."

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"Good data flow and management.""The most valuable feature is the interface, which is user-friendly and intuitive.""The action feature which Tableau has is very useful for us. If we click on one visualization, it will pass the value to another visualization. That interactivity within different visualizations is the most valuable feature of Tableau.""​Data is easily understood at all levels of the company.""Business insights are shared across various departments.""Its ease of use and ability to convert drag and drop gestures into queries.""The ability to create complex calculations.""​Its ease of use and ability to convert drag and drop gestures into queries."

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Cons
"The integration features could be more interesting, more involved.""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.""It should have more compatible and more advanced visualization and machine learning libraries.""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.""It would be very helpful if Databricks could integrate with platforms in addition to Azure.""Databricks is an analytics platform. It should offer more data science. It should have more features for data scientists to work with.""Pricing is one of the things that could be improved.""The product needs samples and templates to help invite users to see results and understand what the product can do."

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"Requires a lot of user training.""The charts in Tableau are quite limited.""The pricing is a bit higher than the competition. They'll need to lower it to stay competitive.""​Conditional formatting could be an interesting feature to provide to final users.""The data preparation/blending options are very basic. They could be improved.""Tableau is a company that does not respect partners.""Reports should be downloadable as PDF files.""I am a BI consultant. I have worked on different reporting tools, such as Power BI and MicroStrategy. As compared to other tools, Tableau lags behind in handling huge enterprise-level data in terms of robust security and the single integrated metadata concept. When we connect to large or very big databases, then performance-wise, I sometimes found Tableau a little bit slow. It can have the single metadata concept like other tools for the reusability of the objects in multiple reports."

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Pricing and Cost Advice
"Whenever we want to find the actual costing, we have to send an email to Databricks, so having the information available on the internet would be helpful.""I do not exactly know the costs, but one of our clients pays between $100 USD and $200 USD monthly.""Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery.""We find Databricks to be very expensive, although this improved when we found out how to shut it down at night.""The pricing depends on the usage itself.""I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself.""The price is okay. It's competitive.""Databricks uses a price-per-use model, where you can use as much compute as you need."

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"The company chose to purchase a creator license for me, which was $70. With that license, you can also be an administrator. We also have 20-25 extra licenses and they cost around $20-$35 each. Those are for normal users who will be viewing the dashboards. Those are monthly charges.""Tableau's licensing is pretty straightforward and simple.""ROI is very high, but it requires a data preparation/blending tool.""The cost of the solution should be improved.""It is reasonable and cheap as compared to other major tools. It has a good price, and people go for it because of its pricing.""Pricing is not bad. It's competitive.""At $70 per month, I think the price is a bit scary. I have a small consulting firm in Ghana, working in about 15 different African countries, and when it comes to our part of the world, $70 a month is a lot of money for software.""The professional version of Tableau is quite expensive."

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Comparison Review
Guillermo (Bill) Cabiro
I do use both Tableau and QlikView. Although very different, I really like both solutions. They belong to the new BI generation known as Interactive Visual Analytics. In my opinion, QlikView has a more intuitive interface for regular users or executives that are not technical experts but the development side is a little more complex. Up to version 12 QlikView did not provide drag & drop features. If a user wanted to see something not included in the application the new object had to be created by a power user or developer because Qlikview's scripting has somewhat of a learning curve. On the positive side, QlikView's scripting is a great asset as it functions as an ETL allowing the integration of hundreds of different data sources into the same visual app. Another feature that’s extremely useful is Qlik’s proprietary Associative Model that allows the users to visualize data relationships that exist as well as those that do not. Tableau on the other hand is a lot easier to use for developers, analysts or power users who need to connect, manipulate and visualize data rather quickly. While this makes Tableau a better fit for the more analytical crowd, it may not be as appealing or intuitive to the regular or casual business users as QlikView is. Tableau has full pivot, drag & drop and drill down capabilities that are great for developers or power users. They can rotate measures and dimensions and graph them instantly using visualization best practices as suggested by… Read more »
Questions from the Community
Top Answer: Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with… more »
Top Answer: Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their… more »
Top Answer: The initial setup is pretty easy.
Top Answer: It depends on the Data architecture and the complexity of your requirement. Some great tools in the market are Qlik Sense, Power BI, OBIEE, Tableau, etc. I have recently started using Cognos… more »
Top Answer: Both tools have their positives and negatives. First, I should mention that I am relatively new to Tableau. I have been working on and off Tableau for about a year, but getting to work on it… more »
Top Answer: It is easy to use, and it can handle a large amount of data.
Ranking
2nd
Views
29,064
Comparisons
24,210
Reviews
24
Average Words per Review
552
Rating
8.0
Views
44,552
Comparisons
35,986
Reviews
55
Average Words per Review
618
Rating
8.1
Comparisons
Also Known As
Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
Tableau Desktop, Tableau Server, Tableau Online
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Overview

Databricks creates a Unified Analytics Platform that accelerates innovation by unifying data science, engineering, and business. It utilizes Apache Spark to help clients with cloud-based big data processing. It puts Spark on “autopilot” to significantly reduce operational complexity and management cost. The Databricks I/O module (DBIO) improves the read and write performance of Apache Spark in the cloud. An increase in productivity is ensured through Databricks’ collaborative workplace.

Tableau helps people and organizations become more data-driven as the trusted leader in analytics.

The Tableau platform provides the breadth and depth of capabilities to serve the needs of even the largest global enterprises in a seamless, integrated experience. Tableau is designed to fit, not dictate your data strategy, and adapts to your environment with unmatched flexibility and choice, while meeting the toughest governance and security requirements.

People love using Tableau because it is both powerful and intuitive—and offers a fundamentally different user experience by empowering people of all skill levels to explore and analyze data using visuals and natural language. Tableau has become the standard language of analytics for modern business users and continues to lead the industry with the most passionate and engaged user community in analytics, a customer base with millions of users at more than 80,000 organizations, and a deep commitment to customer-focused innovation

Evaluation Guide: How to choose the right BI & analytics platform

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Sample Customers
Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
Accenture, Adobe, Amazon.com, Bank of America, Charles Schwab Corp, Citigroup, Coca-Cola Company, Cornell University, Dell, Deloitte, Duke University, eBay, Exxon Mobil, Fannie Mae, Ferrari, French Red Cross, Goldman Sachs, Google, Government of Canada, HP, Intel, Johns Hopkins Hospital, Macy's, Merck, The New York Times, PayPal, Pfizer, US Army, US Air Force, Skype, and Walmart.
Top Industries
REVIEWERS
Financial Services Firm20%
Computer Software Company20%
Energy/Utilities Company10%
Consumer Goods Company10%
VISITORS READING REVIEWS
Computer Software Company28%
Comms Service Provider15%
Financial Services Firm8%
Media Company5%
REVIEWERS
Financial Services Firm14%
Healthcare Company8%
Energy/Utilities Company8%
University7%
VISITORS READING REVIEWS
Computer Software Company25%
Comms Service Provider14%
Financial Services Firm10%
Government7%
Company Size
REVIEWERS
Small Business13%
Midsize Enterprise21%
Large Enterprise67%
VISITORS READING REVIEWS
Small Business26%
Midsize Enterprise18%
Large Enterprise57%
REVIEWERS
Small Business29%
Midsize Enterprise19%
Large Enterprise52%
VISITORS READING REVIEWS
Small Business25%
Midsize Enterprise17%
Large Enterprise58%
Find out what your peers are saying about Databricks vs. Tableau and other solutions. Updated: January 2021.
542,721 professionals have used our research since 2012.

Databricks is ranked 2nd in Data Science Platforms with 24 reviews while Tableau is ranked 2nd in Business Intelligence (BI) Tools with 63 reviews. Databricks is rated 8.0, while Tableau is rated 8.0. The top reviewer of Databricks writes "Has a good feature set but it needs samples and templates to help invite users to see results". On the other hand, the top reviewer of Tableau writes "Lets me train new users quickly, easily, and intuitively". Databricks is most compared with Microsoft Azure Machine Learning Studio, Amazon SageMaker, Azure Stream Analytics, Alteryx and Anaconda, whereas Tableau is most compared with Microsoft BI, SAP Analytics Cloud, MicroStrategy, ELK Kibana and Oracle OBIEE. See our Databricks vs. Tableau report.

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.