What users are saying about
50 Ratings
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Score 8.7 out of 100
9 Ratings
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Score 8.7 out of 100

Feature Set Ratings

    Platform Connectivity

    Databricks Lakehouse Platform

    Feature Set Not Supported
    N/A
    8.0

    H2O

    80%
    H2O ranks higher in 2/2 features

    Connect to Multiple Data Sources

    N/A
    0 Ratings
    8.0
    80%
    1 Rating

    Automatic Data Format Detection

    N/A
    0 Ratings
    8.0
    80%
    1 Rating

    Data Exploration

    Databricks Lakehouse Platform

    Feature Set Not Supported
    N/A
    8.5

    H2O

    85%
    H2O ranks higher in 2/2 features

    Visualization

    N/A
    0 Ratings
    8.0
    80%
    1 Rating

    Interactive Data Analysis

    N/A
    0 Ratings
    9.0
    90%
    1 Rating

    Data Preparation

    Databricks Lakehouse Platform

    Feature Set Not Supported
    N/A
    9.3

    H2O

    93%
    H2O ranks higher in 3/3 features

    Interactive Data Cleaning and Enrichment

    N/A
    0 Ratings
    10.0
    100%
    1 Rating

    Data Transformations

    N/A
    0 Ratings
    9.0
    90%
    1 Rating

    Built-in Processors

    N/A
    0 Ratings
    9.0
    90%
    1 Rating

    Platform Data Modeling

    Databricks Lakehouse Platform

    Feature Set Not Supported
    N/A
    10.0

    H2O

    100%
    H2O ranks higher in 4/4 features

    Multiple Model Development Languages and Tools

    N/A
    0 Ratings
    10.0
    100%
    1 Rating

    Automated Machine Learning

    N/A
    0 Ratings
    10.0
    100%
    1 Rating

    Single platform for multiple model development

    N/A
    0 Ratings
    10.0
    100%
    1 Rating

    Self-Service Model Delivery

    N/A
    0 Ratings
    10.0
    100%
    1 Rating

    Model Deployment

    Databricks Lakehouse Platform

    Feature Set Not Supported
    N/A
    9.0

    H2O

    90%
    H2O ranks higher in 2/2 features

    Flexible Model Publishing Options

    N/A
    0 Ratings
    10.0
    100%
    1 Rating

    Security, Governance, and Cost Controls

    N/A
    0 Ratings
    8.0
    80%
    1 Rating

    Attribute Ratings

    • Databricks Lakehouse Platform (Unified Analytics Platform) is rated higher in 1 area: Likelihood to Recommend
    • H2O is rated higher in 1 area: Support Rating

    Likelihood to Recommend

    8.7

    Databricks Lakehouse Platform

    87%
    15 Ratings
    8.1

    H2O

    81%
    3 Ratings

    Usability

    9.0

    Databricks Lakehouse Platform

    90%
    3 Ratings

    H2O

    N/A
    0 Ratings

    Support Rating

    7.5

    Databricks Lakehouse Platform

    75%
    2 Ratings
    9.0

    H2O

    90%
    2 Ratings

    Contract Terms and Pricing Model

    8.0

    Databricks Lakehouse Platform

    80%
    1 Rating

    H2O

    N/A
    0 Ratings

    Professional Services

    10.0

    Databricks Lakehouse Platform

    100%
    1 Rating

    H2O

    N/A
    0 Ratings

    Likelihood to Recommend

    Databricks Lakehouse Platform

    If you need a managed big data megastore, which has native integration with highly optimized Apache Spark Engine and native integration with MLflow, go for Databricks Lakehouse Platform. The Databricks Lakehouse Platform is a breeze to use and analytics capabilities are supported out of the box. You will find it a bit difficult to manage code in notebooks but you will get used to it soon.
    Anonymous | TrustRadius Reviewer

    H2O

    Most suited if in little time you wanted to build and train a model. Then, H2O makes life very simple. It has support with R, Python and Java, so no programming dependency is required to use it. It's very simple to use.If you want to modify or tweak your ML algorithm then H2O is not suitable. You can't develop a model from scratch.
    Anonymous | TrustRadius Reviewer

    Pros

    Databricks Lakehouse Platform

    • 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
    Anonymous | TrustRadius Reviewer

    H2O

    • Excellent analytical and prediction tool
    • In the beginning, usage of H20 Flow in Web UI enables quick development and sharing of the analytical model
    • Readily available algorithms, easy to use in your analytical projects
    • Faster than Python scikit learn (in machine learning supervised learning area)
    • It can be accessed (run) from Python, not only JAVA etc.
    • Well documented and suitable for fast training or self studying
    • In the beginning, one can use the clickable Flow interface (WEB UI) and later move to a Python console. There is then no need to click in H20 Flow
    • It can be used as open source
    Viktor Mulac | TrustRadius Reviewer

    Cons

    Databricks Lakehouse Platform

    • Better Localized Testing
    • When they were primarily OSS Spark; it was easier to test/manage releases versus the newer DB Runtime. Wish there was more configuration in Runtime less pick a version.
    • Graphing Support went non-existent; when it was one of their compelling general engine.
    Anonymous | TrustRadius Reviewer

    H2O

    • Better documentation
    • Improve the Visual presentations including charting etc
    Anonymous | TrustRadius Reviewer

    Pricing Details

    Databricks Lakehouse Platform

    General

    Free Trial
    Free/Freemium Version
    Premium Consulting/Integration Services
    Entry-level set up fee?
    No

    Starting Price

    $0.07 Per DBU

    Databricks Lakehouse Platform Editions & Modules

    Edition
    Standard$0.071
    Premium$0.101
    Enterprise$0.131
    1. Per DBU
    Additional Pricing Details

    H2O

    General

    Free Trial
    Free/Freemium Version
    Premium Consulting/Integration Services
    Entry-level set up fee?
    No

    Starting Price

    H2O Editions & Modules

    Additional Pricing Details

    Usability

    Databricks Lakehouse Platform

    Databricks Lakehouse Platform 9.0
    Based on 3 answers
    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
    Anonymous | TrustRadius Reviewer

    H2O

    No score
    No answers yet
    No answers on this topic

    Support Rating

    Databricks Lakehouse Platform

    Databricks Lakehouse Platform 7.5
    Based on 2 answers
    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.
    Jonatan Bouchard | TrustRadius Reviewer

    H2O

    H2O 9.0
    Based on 2 answers
    The overall experience I have with H2O is really awesome, even with its cost effectiveness.
    Anonymous | TrustRadius Reviewer

    Alternatives Considered

    Databricks Lakehouse Platform

    Databricks has a much better edge than Synapse in hundred different ways. Databricks has Photon engine, faster available release in cloud and databricks does not run on Open source spark version so better optimization, better performance and better agility and all kind of performance boost can be achieved in Databricks rather Open source synapse spark
    Anonymous | TrustRadius Reviewer

    H2O

    Both are open source (though H2O only up to some level). Both comprise of deep learning, but H2O is not focused directly on deep learning, while Tensor Flow has a "laser" focus on deep learning. H2O is also more focused on scalability. H2O should be looked at not as a competitor but rather a complementary tool. The use case is usually not only about the algorithms, but also about the data model and data logistics and accessibility. H2O is more accessible due to its UI. Also, both can be accessed from Python. The community around TensorFlow seems larger than that of H2O.
    Viktor Mulac | TrustRadius Reviewer

    Contract Terms and Pricing Model

    Databricks Lakehouse Platform

    Databricks Lakehouse Platform 8.0
    Based on 1 answer
    The problem with this tool and all other ones that are at the top of the industry, it's so expensive that soon as another one will be on the market and deliver the same or different value, it will be catastrophic for them. So you get the fact that they are cashing every dime right now like SAS or Hadoop once did. Now, look at them
    Jonatan Bouchard | TrustRadius Reviewer

    H2O

    No score
    No answers yet
    No answers on this topic

    Professional Services

    Databricks Lakehouse Platform

    Databricks Lakehouse Platform 10.0
    Based on 1 answer
    Again, another level of professional services, this is not their biggest strength but this is the cherry on top. I couldn't think about any other professional services like this one. Now I'm talking about meaningful services that really help out our project and delivery.
    Jonatan Bouchard | TrustRadius Reviewer

    H2O

    No score
    No answers yet
    No answers on this topic

    Return on Investment

    Databricks Lakehouse Platform

    • Machine learning is a very new concept and not many universities offer to teach it. My school and a few others have been utilizing Databricks as one of the tools to teach and learn machine learning. By doing this, my university is creating a strong future workforce for the job market.
    Ann Le | TrustRadius Reviewer

    H2O

    • Positive impact: saving in infrastructure expenses - compared to other bulky tools this costs a fraction
    • Positive impact: ability to get quick fixes from H2O when problems arise - compared to waiting for several months/years for new releases from other vendors
    • Positive impact: Access to H2O core team and able to get features that are needed for our business quickly added to the core H2O product
    Anonymous | TrustRadius Reviewer

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