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Cloudera Data Science Workbench vs. Databricks Data Intelligence Platform

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Data Science Workbench

    Score6.7 out of 10
    N/ACloudera Data Science Workbench enables secure self-service data science for the enterprise. It is a collaborative environment where developers can work with a variety of libraries and frameworks.N/A

    Databricks Data Intelligence Platform

    Score8.4 out of 10
    N/ADatabricks in San Francisco offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service aims to provide a reliable and scalable platform for data pipelines, data lakes, and data platforms. Users can manage full data journey, to ingest, process, store, and expose data throughout an organization. Its Data Science Workspace is a collaborative environment for practitioners to run…

    $0.07

    Per DBU

    Pricing
    Data Science WorkbenchDatabricks Data Intelligence Platform
    Editions & Modules
    No answers on this topic
    Standard
    $0.07
    Per DBU
    Premium
    $0.10
    Per DBU
    Enterprise
    $0.13
    Per DBU
    Offerings
    Pricing Offerings
    Data Science WorkbenchDatabricks Data Intelligence Platform
    Free Trial
    NoNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    Data Science WorkbenchDatabricks Data Intelligence Platform
    Considered Both Products
    Cloudera
    No answer on this topic
    Databricks
    Chose Databricks Data Intelligence Platform
    When we started using it, only the notebook experience was mature. However, DB was very helpful giving us direct support to get onto their platform. Really there was little in the way to compare to them at the time. AWS has services but not the same low-cost angle.
    Incentivized
    Key User Insights
    Would buy again
    No answers on this topic
    100%
    Would buy again
    13 Answers
    Delivers good value for the price
    No answers on this topic
    100%
    Delivers good value for the price
    13 Answers
    Happy with the feature set
    No answers on this topic
    92%
    Happy with the feature set
    12 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    100%
    Lived up to sales and marketing promises
    9 Answers
    Implementation went as expected
    No answers on this topic
    90%
    Implementation went as expected
    9 Answers
    Features
    Data Science WorkbenchDatabricks Data Intelligence Platform
    Platform Connectivity
    Comparison of Platform Connectivity features of Cloudera Data Science Workbench and Databricks Data Intelligence Platform
    Feature
    Cloudera Data Science Workbench
    7.5
    2 Ratings
    11% below category average
    Databricks Data Intelligence Platform
    -
    Ratings
    Connect to Multiple Data Sources7.02 Ratings00 Ratings
    Extend Existing Data Sources8.02 Ratings00 Ratings
    Automatic Data Format Detection7.02 Ratings00 Ratings
    MDM Integration8.02 Ratings00 Ratings
    Data Exploration
    Comparison of Data Exploration features of Cloudera Data Science Workbench and Databricks Data Intelligence Platform
    Feature
    Cloudera Data Science Workbench
    7.6
    2 Ratings
    10% below category average
    Databricks Data Intelligence Platform
    -
    Ratings
    Visualization7.12 Ratings00 Ratings
    Interactive Data Analysis8.02 Ratings00 Ratings
    Data Preparation
    Comparison of Data Preparation features of Cloudera Data Science Workbench and Databricks Data Intelligence Platform
    Feature
    Cloudera Data Science Workbench
    7.8
    2 Ratings
    4% below category average
    Databricks Data Intelligence Platform
    -
    Ratings
    Interactive Data Cleaning and Enrichment7.02 Ratings00 Ratings
    Data Transformations8.02 Ratings00 Ratings
    Data Encryption8.02 Ratings00 Ratings
    Built-in Processors8.02 Ratings00 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of Cloudera Data Science Workbench and Databricks Data Intelligence Platform
    Feature
    Cloudera Data Science Workbench
    7.6
    2 Ratings
    10% below category average
    Databricks Data Intelligence Platform
    -
    Ratings
    Multiple Model Development Languages and Tools8.02 Ratings00 Ratings
    Automated Machine Learning7.01 Ratings00 Ratings
    Single platform for multiple model development7.12 Ratings00 Ratings
    Self-Service Model Delivery8.12 Ratings00 Ratings
    Model Deployment
    Comparison of Model Deployment features of Cloudera Data Science Workbench and Databricks Data Intelligence Platform
    Feature
    Cloudera Data Science Workbench
    8.0
    2 Ratings
    6% below category average
    Databricks Data Intelligence Platform
    -
    Ratings
    Flexible Model Publishing Options8.12 Ratings00 Ratings
    Security, Governance, and Cost Controls7.82 Ratings00 Ratings
    Best Alternatives
    Data Science WorkbenchDatabricks Data Intelligence Platform
    Small Businesses
    RapidMiner
    Score8.9 out of 10
    No answers on this topic
    Medium-sized Companies
    Anaconda
    Score8.1 out of 10
    No answers on this topic
    Enterprises
    IBM Watson Studio
    Score10 out of 10
    No answers on this topic
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Data Science WorkbenchDatabricks Data Intelligence Platform
    Likelihood to Recommend
    9.0
    (3 ratings)
    10.0
    (18 ratings)
    Usability
    -
    (0 ratings)
    10.0
    (4 ratings)
    Support Rating
    7.9
    (2 ratings)
    8.7
    (2 ratings)
    Contract Terms and Pricing Model
    -
    (0 ratings)
    8.0
    (1 ratings)
    Professional Services
    -
    (0 ratings)
    10.0
    (1 ratings)
    User Testimonials
    Data Science WorkbenchDatabricks Data Intelligence Platform
    Likelihood to Recommend
    Cloudera
    Organizations which already implemented on-premise Hadoop based Cloudera Data Platform (CDH) for their Big Data warehouse architecture will definitely get more value from seamless integration of Cloudera Data Science Workbench (CDSW) with their existing CDH Platform. However, for organizations with hybrid (cloud and on-premise) data platform without prior implementation of CDH, implementing CDSW can be a challenge technically and financially.
    Incentivized
    Read full review
    Databricks
    Medium to Large data throughput shops will benefit the most from Databricks Spark processing. Smaller use cases may find the barrier to entry a bit too high for casual use cases. Some of the overhead to kicking off a Spark compute job can actually lead to your workloads taking longer, but past a certain point the performance returns cannot be beat.
    Incentivized
    Read full review
    Pros
    Cloudera
    • One single IDE (browser based application) that makes Scala, R, Python integrated under one tool
    • For larger organizations/teams, it lets you be self reliant
    • As it sits on your cluster, it has very easy access of all the data on the HDFS
    • Linking with Github is a very good way to keep the code versions intact
    Incentivized
    Read full review
    Databricks
    • Process raw data in One Lake (S3) env to relational tables and views
    • Share notebooks with our business analysts so that they can use the queries and generate value out of the data
    • Try out PySpark and Spark SQL queries on raw data before using them in our Spark jobs
    • Modern day ETL operations made easy using Databricks. Provide access mechanism for different set of customers
    Incentivized
    Read full review
    Cons
    Cloudera
    • Installation is difficult.
    • Upgrades are difficult.
    • Licensing options are not flexible.
    Incentivized
    Read full review
    Databricks
    • Connect my local code in Visual code to my Databricks Lakehouse Platform cluster so I can run the code on the cluster. The old databricks-connect approach has many bugs and is hard to set up. The new Databricks Lakehouse Platform extension on Visual Code, doesn't allow the developers to debug their code line by line (only we can run the code).
    • Maybe have a specific Databricks Lakehouse Platform IDE that can be used by Databricks Lakehouse Platform users to develop locally.
    • Visualization in MLFLOW experiment can be enhanced
    Incentivized
    Read full review
    Usability
    Cloudera
    No answers on this topic
    Databricks
    Because it is an amazing platform for designing experiments and delivering a deep dive analysis that requires execution of highly complex queries, as well as it allows to share the information and insights across the company with their shared workspaces, while keeping it secured.

    in terms of graph generation and interaction it could improve their UI and UX
    Incentivized
    Read full review
    Support Rating
    Cloudera
    Cloudera Data Science Workbench has excellence online resources support such as documentation and examples. On top of that the enterprise license also comes with SLA on opening a ticket to Cloudera Services and support for complaint handling and troubleshooting by email or through a phone call. On top of that it also offers additional paid training services.
    Incentivized
    Read full review
    Databricks
    One of the best customer and technology support that I have ever experienced in my career. You pay for what you get and you get the Rolls Royce. It reminds me of the customer support of SAS in the 2000s when the tools were reaching some limits and their engineer wanted to know more about what we were doing, long before "data science" was even a name. Databricks truly embraces the partnership with their customer and help them on any given challenge.
    Read full review
    Alternatives Considered
    Cloudera
    Both the tools have similar features and have made it pretty easy to install/deploy/use. Depending on your existing platform (Cloudera vs. Azure) you need to pick the Workbench. Another observation is that Cloudera has better support where you can get feedback on your questions pretty fast (unlike MS). As its a new product, I expect MS to be more efficient in handling customers questions.
    Incentivized
    Read full review
    Databricks
    The most important differentiating factor for Databricks Lakehouse Platform from these other platforms is support for ACID transactions and the time travel feature. Also, native integration with managed MLflow is a plus. EMR, Cloudera, and Hortonworks are not as optimized when it comes to Spark Job Execution. Other platforms need to be self-managed, which is another huge hassle.
    Incentivized
    Read full review
    Return on Investment
    Cloudera
    • Paid off for demonstration purposes.
    Incentivized
    Read full review
    Databricks
    • The ability to spin up a BIG Data platform with little infrastructure overhead allows us to focus on business value not admin
    • DB has the ability to terminate/time out instances which helps manage cost.
    • The ability to quickly access typical hard to build data scenarios easily is a strength.
    Incentivized
    Read full review
    ScreenShots