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Databricks Data Intelligence Platform vs. Domino Enterprise MLOps Platform

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Databricks Data Intelligence Platform

    Score8.5 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

    Domino Enterprise MLOps Platform

    Score8 out of 10
    Enterprise companies (1,001+ employees)
    The Domino Enterprise MLOps Platform helps data science teams improve the speed, quality and impact of data science at scale. Domino is presented as open and flexible, to empower professional data scientists to use their preferred tools and infrastructure. Data science models get into production fast and are kept operating at peak performance with integrated workflows. Domino also delivers the security, governance and compliance that enterprises expect. The Domino Enterprise MLOps…N/A
    Pricing
    Databricks Data Intelligence PlatformDomino Enterprise MLOps Platform
    Editions & Modules
    Standard
    $0.07
    Per DBU
    Premium
    $0.10
    Per DBU
    Enterprise
    $0.13
    Per DBU
    No answers on this topic
    Offerings
    Pricing Offerings
    Databricks Data Intelligence PlatformDomino Enterprise MLOps Platform
    Free Trial
    NoYes
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details
    More Pricing Information
    Community Pulse
    Databricks Data Intelligence PlatformDomino Enterprise MLOps Platform
    Considered Both Products
    Databricks
    No answer on this topic
    Domino Data Lab
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    13 Answers
    No answers on this topic
    Delivers good value for the price
    100%
    Delivers good value for the price
    13 Answers
    No answers on this topic
    Happy with the feature set
    92%
    Happy with the feature set
    12 Answers
    No answers on this topic
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    9 Answers
    No answers on this topic
    Implementation went as expected
    90%
    Implementation went as expected
    9 Answers
    No answers on this topic
    User Ratings
    Databricks Data Intelligence PlatformDomino Enterprise MLOps Platform
    Likelihood to Recommend
    10.0
    (18 ratings)
    -
    (0 ratings)
    Usability
    10.0
    (4 ratings)
    -
    (0 ratings)
    Support Rating
    8.7
    (2 ratings)
    -
    (0 ratings)
    Contract Terms and Pricing Model
    8.0
    (1 ratings)
    -
    (0 ratings)
    Professional Services
    10.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    Databricks Data Intelligence PlatformDomino Enterprise MLOps Platform
    Likelihood to Recommend
    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
    Domino Data Lab
    No answers on this topic
    Pros
    Databricks
    No answers on this topic
    Domino Data Lab
    No answers on this topic
    Cons
    Databricks
    No answers on this topic
    Domino Data Lab
    No answers on this topic
    Usability
    Databricks
    No answers on this topic
    Domino Data Lab
    No answers on this topic
    Support Rating
    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
    Domino Data Lab
    No answers on this topic
    Alternatives Considered
    Databricks
    No answers on this topic
    Domino Data Lab
    No answers on this topic
    Return on Investment
    Databricks
    No answers on this topic
    Domino Data Lab
    No answers on this topic
    ScreenShots

    Domino Enterprise MLOps Platform Screenshots

    Screenshot of The Domino Enterprise MLOps Platform helps data science teams improve the speed, quality and impact of data science at scale.Screenshot of The Self-Service Infrastructure Portal makes data science teams more productive with access to their preferred tools, scalable compute, and diverse data sets. By automating time-consuming DevOps tasks, data scientists can focus on the tasks at hand.Screenshot of The Integrated Model Factory includes a workbench, model and app deployment, and integrated monitoring to rapidly experiment, deploy the best models in production, ensure optimal performance, and collaborate across the end-to-end data science lifecycle.Screenshot of The System of Record has a reproducibility engine, search and knowledge management, and integrated project management. Teams can find, reuse, reproduce, and build on any data science work to amplify innovation.Screenshot of Model monitoring capabilities ensure that all production models maintain peak performance. Automated alerts provide notification when data and quality drift occurs so users can re-train, rebuild, and re-publish the model.Screenshot of Nexus is a single pane of glass to run data science and ML workloads across any compute cluster — in any cloud, region, or on-premises. It unifies data science silos across the enterprise, providing one place to build, deploy, and monitor models.