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Databricks Data Intelligence Platform vs. IBM Cloud Functions

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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

    IBM Cloud Functions

    Score6.5 out of 10
    N/AIBM Cloud Functions is a PaaS platform based on Apache OpenWhisk. With it, developers write code (“actions”) that respond to external events. Actions are hosted, executed, and scaled on demand based on the number of events coming in. No servers or infrastructure to provision and manage.

    $0

    per second of execution

    Pricing
    Databricks Data Intelligence PlatformIBM Cloud Functions
    Editions & Modules
    Standard
    $0.07
    Per DBU
    Premium
    $0.10
    Per DBU
    Enterprise
    $0.13
    Per DBU
    Basic Cloud Functions Rate
    $0.00017
    per second of execution
    API Gateway Rate
    Free
    Offerings
    Pricing Offerings
    Databricks Data Intelligence PlatformIBM Cloud Functions
    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 PlatformIBM Cloud Functions
    Considered Both Products
    Databricks
    No answer on this topic
    IBM
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    16 Answers
    No answers on this topic
    Delivers good value for the price
    100%
    Delivers good value for the price
    16 Answers
    No answers on this topic
    Happy with the feature set
    94%
    Happy with the feature set
    15 Answers
    No answers on this topic
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    10 Answers
    No answers on this topic
    Implementation went as expected
    92%
    Implementation went as expected
    12 Answers
    No answers on this topic
    Best Alternatives
    Databricks Data Intelligence PlatformIBM Cloud Functions
    Small Businesses
    No answers on this topic
    AWS Lambda
    Score8.3 out of 10
    Medium-sized Companies
    SAP Business Data Cloud
    Score8.6 out of 10
    AWS Lambda
    Score8.3 out of 10
    Enterprises
    SAP Business Data Cloud
    Score8.6 out of 10
    AWS Lambda
    Score8.3 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Databricks Data Intelligence PlatformIBM Cloud Functions
    Likelihood to Recommend
    9.4
    (21 ratings)
    3.0
    (7 ratings)
    Usability
    9.7
    (7 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 PlatformIBM Cloud Functions
    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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    IBM
    IBM Cloud Functions [is] not the worse product on the IBM cloud. I decided to write this review as I thought it would be balanced. I would still use functions to set up a serverless architecture where execution time is pretty quick and the code is relatively simple. I wouldn't use IBM Cloud Functions for async calls obviously, as costs could be higher. The functions documentation is lacking in terms of CI/CD, and there are unexplainable errors occurring - like the network connection that I mentioned. So I wouldn't just rely on IBM Cloud Functions too much for the entire system, but make sure it's diversified.
    Read full review
    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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    IBM
    • Great substitute for a simple API calls to run non-complicated code.
    • Easy way to run Python/Java/Javascript to get something done.
    • File validation.
    Incentivized
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    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
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    IBM
    • Billing can be a hassle, not the most responsive customer service/support team
    • Handles & executes most functionalities, but other platforms offer more scalability if you're seeking consistent and stable growth
    Incentivized
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    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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    IBM
    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
    IBM
    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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    IBM
    • ICF is a lightweight service and does not require runtime configurations
    • Scalable on demand and hence there is no need to pay for runtime costs
    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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    IBM
    • It directly affected our expenses since we do not need to deploy and maintain a set of separate applications.
    • It allowed us to pay for only the amount of time cloud functions run.
    • It saved on maintenance and monitoring of the applications it replaced.
    Incentivized
    Read full review
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