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Cloudera Data Science Workbench vs Databricks comparison

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Featured Review
Find out what your peers are saying about Alteryx, Databricks, Knime and others in Data Science Platforms. Updated: January 2022.
564,599 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
"The Cloudera Data Science Workbench is customizable and easy to use."

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"The built-in optimization recommendations halved the speed of queries and allowed us to reach decision points and deliver insights very quickly.""It's easy to increase performance as required.""The solution is very easy to use.""It can send out large data amounts.""Can cut across the entire ecosystem of open source technology to give an extra level of getting the transformatory process of the data.""The time travel feature is the solution's most valuable aspect.""One of the features provides nice interactive clusters, or compute instances that you don't really need to manage often.""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."

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Cons
"Running this solution requires a minimum of 12GB to 16GB of RAM."

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"The product needs samples and templates to help invite users to see results and understand what the product can do.""The interface of Databricks could be easier to use when compared to other solutions. It is not easy for non-data scientists. The user interface is important before we had to write code manually and as solutions move to "No code AI" it is critical that the interface is very good.""The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment.""There would also be benefits if more options were available for workers, or the clusters of the two points.""The integration of data could be a bit better.""I have seen better user interfaces, so that is something that can be improved.""I would like to see more documentation in terms of how an end-user could use it, and users like me can easily try it and implement use cases.""Databricks requires writing code in Python or SQL, so if you're a good programmer then you can use Databricks."

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Pricing and Cost Advice
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  • "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."
  • "There are different versions."
  • "The solution uses a pay-per-use model with an annual subscription fee or package. Typically this solution is used on a cloud platform, such as Azure or AWS, but more people are choosing Azure because the price is more reasonable."
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    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 »
    Ranking
    15th
    Views
    3,643
    Comparisons
    3,100
    Reviews
    1
    Average Words per Review
    302
    Rating
    8.0
    2nd
    Views
    30,779
    Comparisons
    25,469
    Reviews
    22
    Average Words per Review
    531
    Rating
    7.9
    Comparisons
    Also Known As
    CDSW
    Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
    Learn More
    Overview

    Cloudera Data Science Workbench (CDSW) makes secure, collaborative data science at scale a reality for the enterprise and accelerates the delivery of new data products. With CDSW, organizations can research and experiment faster, deploy models easily and with confidence, as well as rely on the wider Cloudera platform to reduce the risks and costs of data science projects. Access any data anywhere – from cloud object storage to data warehouses, CDSW provides connectivity not only to CDH but the systems your data science teams rely on for analysis.

    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.

    Offer
    Learn more about Cloudera Data Science Workbench
    Learn more about Databricks
    Sample Customers
    IQVIA, Rush University Medical Center, Western Union
    Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
    Top Industries
    VISITORS READING REVIEWS
    Computer Software Company25%
    Financial Services Firm18%
    Comms Service Provider14%
    Insurance Company5%
    REVIEWERS
    Financial Services Firm14%
    Computer Software Company14%
    Mining And Metals Company14%
    Energy/Utilities Company7%
    VISITORS READING REVIEWS
    Computer Software Company27%
    Comms Service Provider15%
    Financial Services Firm8%
    Government5%
    Company Size
    No Data Available
    REVIEWERS
    Small Business14%
    Midsize Enterprise17%
    Large Enterprise69%
    VISITORS READING REVIEWS
    Small Business26%
    Midsize Enterprise19%
    Large Enterprise55%
    Find out what your peers are saying about Alteryx, Databricks, Knime and others in Data Science Platforms. Updated: January 2022.
    564,599 professionals have used our research since 2012.

    Cloudera Data Science Workbench is ranked 15th in Data Science Platforms with 1 review while Databricks is ranked 2nd in Data Science Platforms with 23 reviews. Cloudera Data Science Workbench is rated 8.0, while Databricks is rated 7.8. The top reviewer of Cloudera Data Science Workbench writes "Customizable, easy to install, and easy to use". On the other hand, the top reviewer of Databricks writes "Has a good feature set but it needs samples and templates to help invite users to see results". Cloudera Data Science Workbench is most compared with Dataiku Data Science Studio, Amazon SageMaker, Anaconda, Microsoft Azure Machine Learning Studio and Alteryx, whereas Databricks is most compared with Microsoft Azure Machine Learning Studio, Amazon SageMaker, Azure Stream Analytics, Alteryx and Apache Flink.

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