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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Databricks Data Intelligence Platform

    Score9 out of 10
    N/ADatabricks offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service provides a platform for data pipelines, data lakes, and data platforms.

    $0.07

    Per DBU

    Kubernetes

    Score9.1 out of 10
    N/AKubernetes is an open-source container cluster manager.N/A
    Pricing
    Databricks Data Intelligence PlatformKubernetes
    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 PlatformKubernetes
    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
    Databricks Data Intelligence PlatformKubernetes
    Considered Both Products
    Databricks
    No answer on this topic
    Kubernetes
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    16 Answers
    100%
    Would buy again
    9 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    16 Answers
    100%
    Delivers good value for the price
    9 Answers
    Happy with the feature set
    94%
    Happy with the feature set
    15 Answers
    100%
    Happy with the feature set
    9 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    10 Answers
    100%
    Lived up to sales and marketing promises
    5 Answers
    Implementation went as expected
    92%
    Implementation went as expected
    12 Answers
    75%
    Implementation went as expected
    6 Answers
    Features
    Databricks Data Intelligence PlatformKubernetes
    Container Management
    Comparison of Container Management features of Databricks Data Intelligence Platform and Kubernetes
    Feature
    Databricks Data Intelligence Platform
    -
    Ratings
    Kubernetes
    9.2
    4 Ratings
    12% above category average
    Security and Isolation00 Ratings9.34 Ratings
    Container Orchestration00 Ratings9.84 Ratings
    Cluster Management00 Ratings9.84 Ratings
    Storage Management00 Ratings8.64 Ratings
    Resource Allocation and Optimization00 Ratings8.84 Ratings
    Discovery Tools00 Ratings9.34 Ratings
    Update Rollouts and Rollbacks00 Ratings9.34 Ratings
    Self-Healing and Recovery00 Ratings9.33 Ratings
    Analytics, Monitoring, and Logging00 Ratings9.14 Ratings
    Best Alternatives
    Databricks Data Intelligence PlatformKubernetes
    Small Businesses
    No answers on this topic
    Mirantis Kubernetes Engine
    Score8 out of 10
    Medium-sized Companies
    SAP Business Data Cloud
    Score8.6 out of 10
    Amazon Elastic Container Service (Amazon ECS)
    Score8.6 out of 10
    Enterprises
    SAP Business Data Cloud
    Score8.6 out of 10
    SUSE Rancher
    Score9.4 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Databricks Data Intelligence PlatformKubernetes
    Likelihood to Recommend
    9.4
    (21 ratings)
    8.7
    (19 ratings)
    Likelihood to Renew
    -
    (0 ratings)
    10.0
    (1 ratings)
    Usability
    9.7
    (7 ratings)
    9.1
    (3 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 PlatformKubernetes
    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
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    Kubernetes
    K8s should be avoided - If your application works well without being converted into microservices-based architecture & fits correctly in a VM, needs less scaling, have a fixed traffic pattern then it is better to keep away from Kubernetes. Otherwise, the operational challenges & technical expertise will add a lot to the OPEX. Also, if you're the one who thinks that containers consume fewer resources as compared to VMs then this is not true. As soon as you convert your application to a microservice-based architecture, a lot of components will add up, shooting your resource consumption even higher than VMs so, please beware. Kubernetes is a good choice - When the application needs quick scaling, is already in microservice-based architecture, has no fixed traffic pattern, most of the employees already have desired skills.
    Incentivized
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    Pros
    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
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    Kubernetes
    • Complex cluster management can be done with simple commands with strong authentication and authorization schemes
    • Exhaustive documentation and open community smoothens the learning process
    • As a user a few concepts like pod, deployment and service are sufficient to go a long way
    Incentivized
    Read full review
    Cons
    Databricks
    • Sometimes, when multiple jobs depend on each other in different environments, it is not always easy to see the full workflow in one place.
    • It is sometimes difficult to determine which job or cluster contributes more to the overall cost.
    • For beginners, cluster configuration may be a little difficult. So more recommendation in the platform can help.
    Incentivized
    Read full review
    Kubernetes
    • Local development, Kubernetes does tend to be a bit complicated and unnecessary in environments where all development is done locally.
    • The need for add-ons, Helm is almost required when running Kubernetes. This brings a whole new tool to manage and learn before a developer can really start to use Kubernetes effectively.
    • Finicy configmap schemes. Kubernetes configmaps often have environment breaking hangups. The fail safes surrounding configmaps are sadly lacking.
    Incentivized
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    Likelihood to Renew
    Databricks
    No answers on this topic
    Kubernetes
    The Kubernetes is going to be highly likely renewed as the technologies that will be placed on top of it are long term as of planning. There shouldn't be any last minute changes in the adoption and I do not anticipate sudden change of the core underlying technology. It is just that the slow process of technology adoption that makes it hard to switch to something else.
    Read full review
    Usability
    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
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    Kubernetes
    It is an eminently usable platform. However, its popularity is overshadowed by its complexity. To properly leverage the capabilities and possibilities of Kubernetes as a platform, you need to have excellent understanding of your use case, even better understanding of whether you even need Kubernetes, and if yes - be ready to invest in good engineering support for the platform itself
    Incentivized
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    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.
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    Kubernetes
    No answers on this topic
    Alternatives Considered
    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
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    Kubernetes
    Most of the required features for any orchestration tool or framework, which is provided by Kubernetes. After understanding all modules and features of the K8S, it is the best fit for us as compared with others out there.
    Incentivized
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    Return on Investment
    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
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    Kubernetes
    • Because of microservices, Kubernetes makes it easy to find the cost of each application easily.
    • Like every new technology, initially, it took more resources to educate ourselves but over a period of time, I believe it's going to be worth it.
    Incentivized
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    ScreenShots