Databricks vs Tableau comparison

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30,172 views|19,226 comparisons
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Comparison Buyer's Guide
Executive Summary

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.
To learn more, read our detailed Databricks vs. Tableau Report (Updated: April 2023).
763,955 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"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."

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"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."

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Cons
"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."

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"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."

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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."
  • More Databricks Pricing and Cost Advice →

  • "For big business, Tableau could be expensive as having a lot of Tableau server users (entering with a browser to reports) could be a bit expensive."
  • "Best advice on pricing is to anticipate the desire for more licenses once the results of this product are acknowledged in other parts of your company."
  • "Paying for users you never setup or buying expensive desktop licenses for users who can solve their users with web editing on the server are the two biggest expenses."
  • "Buy 50 at a time. Project your use base every three months, and project your requirements forward."
  • "Tableau can be costly (but this can be indefinable, such as user experience vs. cheaper etc.)"
  • "I wish there was more of a subscription model with the pricing when it comes to Tableau, so you can get all the latest version upgrades/features if you pay monthly/annually."
  • "The cost is high."
  • "Deployment of dashboards to viewers and unit supervisors can be prohibitively expensive."
  • More Tableau Pricing and Cost Advice →

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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 the… 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:We researched AWS SageMaker, but in the end, we chose Databricks Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It… 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: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:Tableau is easy to set up and maintain. In about a day it is possible for the entire platform to be deployed for use. This relatively short amount of time can make all the difference for companies… more »
    Ranking
    1st
    Views
    30,172
    Comparisons
    19,226
    Reviews
    47
    Average Words per Review
    446
    Rating
    8.2
    Views
    26,921
    Comparisons
    23,202
    Reviews
    19
    Average Words per Review
    620
    Rating
    8.6
    Comparisons
    Also Known As
    Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
    Tableau Desktop, Tableau Server, Tableau Online
    Learn More
    Overview

    Databricks is an industry-leading data analytics platform which is a one-stop product for all data requirements. Databricks is made by the creators of Apache Spark, Delta Lake, ML Flow, and Koalas. It builds on these technologies to deliver a true lakehouse data architecture, making it a robust platform that is reliable, scalable, and fast. Databricks speeds up innovations by synthesizing storage, engineering, business operations, security, and data science.

    Databricks is integrated with Microsoft Azure, Amazon Web Services, and Google Cloud Platform. This enables users to easily manage a colossal amount of data and to continuously train and deploy machine learning models for AI applications. The platform handles all analytic deployments, ranging from ETL to models training and deployment.

    Databricks deciphers the complexities of processing data to empower data scientists, engineers, and analysts with a simple collaborative environment to run interactive and scheduled data analysis workloads. The program takes advantage of AI’s cost-effectivity, flexibility, and cloud storage.

    Databricks Key Features

    Some of Databricks key features include:

    • Cloud-native: Works well on any prominent cloud provider.
    • Data storage: Stores a broad range of data, including structured, unstructured, and streaming.
    • Self-governance: Built-in governance and security controls.
    • Flexibility: Flexible for small-scale jobs as well as running large-scale jobs like Big Data processing because it’s built from Spark and is specifically optimized for Cloud environments.
    • Data science tools: Production-ready data tooling, from engineering to BI, AI, and ML.
    • Familiar languages: While Databricks is Spark-based, it allows commonly used programming languages like R, SQL, Scala, and Python to be used.
    • Team sharing workspaces: Creates an environment that provides interactive workspaces for collaboration, which allow multiple members to collaborate for data model creation, machine learning, and data extraction.
    • Data source: Performs limitless Big Data analytics by connecting to Cloud providers AWS, Azure, and Google, as well as on-premises SQL servers, JSON and CSV.

    Reviews from Real Users

    Databricks stands out from its competitors for several reasons. Two striking features are its collaborative ability and its ability to streamline multiple programming languages.

    PeerSpot users take note of the advantages of these features. A Chief Research Officer in consumer goods writes, “We work with multiple people on notebooks and it enables us to work collaboratively in an easy way without having to worry about the infrastructure. I think the solution is very intuitive, very easy to use. And that's what you pay for.”

    A business intelligence coordinator in construction notes, “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.”

    An Associate Manager who works in consultancy mentions, “The technology that allows us to write scripts within the solution is extremely beneficial. If I was, for example, able to script in SQL, R, Scala, Apache Spark, or Python, I would be able to use my knowledge to make a script in this solution. It is very user-friendly and you can also process the records and validation point of view. The ability to migrate from one environment to another is useful.”

    Tableau is a tool for data visualization and business intelligence that allows businesses to report insights through easy-to-use, customizable visualizations and dashboards. Tableau makes it exceedingly simple for its customers to organize, manage, visualize, and comprehend data. It enables users to dig deep into the data so that they can see patterns and gain meaningful insights. 

    Make data-driven decisions with confidence thanks to Tableau’s assistance in providing faster answers to queries, solving harder problems more easily, and offering new insights more frequently. Tableau integrates directly to hundreds of data sources, both in the cloud and on premises, making it simpler to begin research. People of various skill levels can quickly find actionable information using Tableau’s natural language queries, interactive dashboards, and drag-and-drop capabilities. By quickly creating strong calculations, adding trend lines to examine statistical summaries, or clustering data to identify relationships, users can ask more in-depth inquiries.

    Tableau has many valuable key features:

    • Tableau dashboards provide a complete view of your data through visualizations, visual objects, text, and more.
    • Tableau provides convenient, real-time options to collaborate with other users and instantly share data in the form of visualizations, sheets, and dashboards. 
    • Tableau ensures connectivity to both live data sources and data extraction from external data sources as in-memory data. This gives users the flexibility to use data from more than one source without any restrictions. 
    • Tableau gives many data source option, ranging from spreadsheets, big data, on-premise files, relational databases, non-relational databases, data warehouses, and big data, to on-cloud data. 
    • Tableau has a lot of pre-installed information on maps, such as cities, postal codes, and administrative boundaries. 
    • Tableau has a foolproof security system based on authentication and permission systems for data connections and user access. Tableau also gives you the freedom to integrate with other security protocols.

    Tableau stands out among its competitors for a number of reasons. Some of these include its fast data access, easy creation of visualizations, and its stability. PeerSpot users take note of the advantages of these features in their reviews:

    Romil S., Deputy General Manager of IT at Nayara Energy, notes, "Its visualizations are good, and its features make the development process a little less time-consuming. It has an in-memory extract feature that allows us to extract data and keep it on the server, and then our users can use it quickly.

    Ariful M., Consulting Practice Partner of Data, Analytics & AI at FH, writes, “Tableau is very flexible and easy to learn. It has drag-and-drop function analytics, and its design is very good.

    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
    Computer Software Company25%
    Financial Services Firm16%
    Retailer9%
    Manufacturing Company9%
    VISITORS READING REVIEWS
    Financial Services Firm14%
    Computer Software Company12%
    Manufacturing Company8%
    Healthcare Company6%
    REVIEWERS
    Financial Services Firm12%
    Computer Software Company12%
    University7%
    Healthcare Company7%
    VISITORS READING REVIEWS
    Educational Organization34%
    Financial Services Firm11%
    Computer Software Company8%
    Manufacturing Company6%
    Company Size
    REVIEWERS
    Small Business27%
    Midsize Enterprise14%
    Large Enterprise58%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise11%
    Large Enterprise71%
    REVIEWERS
    Small Business32%
    Midsize Enterprise18%
    Large Enterprise50%
    VISITORS READING REVIEWS
    Small Business14%
    Midsize Enterprise39%
    Large Enterprise47%
    Buyer's Guide
    Databricks vs. Tableau
    April 2023
    Find out what your peers are saying about Databricks vs. Tableau and other solutions. Updated: April 2023.
    763,955 professionals have used our research since 2012.

    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.

    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.