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Databricks Data Intelligence Platform vs. IBM watsonx.data

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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 watsonx.data

    Score8.4 out of 10
    N/AWatsonx.data is presented as an open, hybrid and governed data store that makes it possible for enterprises to scale analytics and AI with a fit-for-purpose data store, built on an open lakehouse architecture, supported by querying, governance and open data formats to access and share data.N/A
    Pricing
    Databricks Data Intelligence PlatformIBM watsonx.data
    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 PlatformIBM watsonx.data
    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 PlatformIBM watsonx.data
    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
    94%
    Would buy again
    34 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    16 Answers
    100%
    Delivers good value for the price
    30 Answers
    Happy with the feature set
    94%
    Happy with the feature set
    15 Answers
    97%
    Happy with the feature set
    35 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
    23 Answers
    Implementation went as expected
    92%
    Implementation went as expected
    12 Answers
    100%
    Implementation went as expected
    29 Answers
    Best Alternatives
    Databricks Data Intelligence PlatformIBM watsonx.data
    Small Businesses
    No answers on this topic
    No answers on this topic
    Medium-sized Companies
    SAP Business Data Cloud
    Score8.6 out of 10
    SAP Business Data Cloud
    Score8.6 out of 10
    Enterprises
    SAP Business Data Cloud
    Score8.6 out of 10
    SAP Business Data Cloud
    Score8.6 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Databricks Data Intelligence PlatformIBM watsonx.data
    Likelihood to Recommend
    9.4
    (21 ratings)
    8.2
    (34 ratings)
    Likelihood to Renew
    -
    (0 ratings)
    7.3
    (4 ratings)
    Usability
    9.7
    (7 ratings)
    8.0
    (10 ratings)
    Availability
    -
    (0 ratings)
    8.2
    (1 ratings)
    Performance
    -
    (0 ratings)
    8.2
    (1 ratings)
    Support Rating
    8.7
    (2 ratings)
    9.1
    (4 ratings)
    Online Training
    -
    (0 ratings)
    8.2
    (1 ratings)
    Implementation Rating
    -
    (0 ratings)
    8.2
    (1 ratings)
    Configurability
    -
    (0 ratings)
    8.2
    (1 ratings)
    Contract Terms and Pricing Model
    8.0
    (1 ratings)
    -
    (0 ratings)
    Ease of integration
    -
    (0 ratings)
    7.3
    (1 ratings)
    Product Scalability
    -
    (0 ratings)
    7.3
    (1 ratings)
    Professional Services
    10.0
    (1 ratings)
    -
    (0 ratings)
    Vendor post-sale
    -
    (0 ratings)
    8.2
    (1 ratings)
    Vendor pre-sale
    -
    (0 ratings)
    8.2
    (1 ratings)
    User Testimonials
    Databricks Data Intelligence PlatformIBM watsonx.data
    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
    Real-time transaction processing (both reads and writes) is where DataStax Enterprise shines. It's very fast with linear scalability should more resources be needed. Additional nodes are added very easily. DataStax Enterprise on its own (without Solr or Spark enabled) isn't well suited for long complicated reports. The data model doesn't support joining multiple tables together which is common in BI reporting.
    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
    • Datastax Cassandra provides high availability and good performance for a database. It is built on top of open source Apache Cassandra so you can always somewhat understand the internal functioning and why.
    • Datastax Cassandra is fairly simple to start using, you can install/setup your cluster and be productive in 1 day.
    • Datastax Cassandra provides a lot of good detailed documentation, and when starting, the detailed free videos on the Datastax site and documentation are very helpful.
    • Datastax Enterprise Edition of Cassandra provides more tools, good support, and quick response SLA for enterprise business support.
    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
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    IBM
    • Interface do need some improvement to be more intuitive for analysts like me.
    • Configuring multiple data sources can require support, as it isn't easy for new users. So, it can be made easier.
    • Additional ETL features can be added, so users don't have to switch between tools.
    Incentivized
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    Likelihood to Renew
    Databricks
    No answers on this topic
    IBM
    As an open source technology Cassandra can be readily used with or without any commercial support. DataStax provides value-added services and features, and in the end it is up to individual situations to strike a balance between the desirability of such support/service versus the associated cost.
    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
    DataStax has a good community built around it and has amazing scalability options. Though the initial setup is a bit costly, in the long run, it makes up for it. It also has powerful monitoring tools and a clean UI.
    Incentivized
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    Reliability and Availability
    Databricks
    No answers on this topic
    IBM
    good recovery features
    Incentivized
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    Performance
    Databricks
    No answers on this topic
    IBM
    scalable product
    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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    IBM
    We have had a few situations where we caused an outage or something has gone wrong and we are able to get a support person to offer live help within minutes. The escalation process is excellent - the best I've seen - and the support team is incredibly strong. Outside of emergencies, the team is very helpful with general questions and working through data model exercises and the subscription I believe still comes with some hours to help get the data model reviewed.
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    Online Training
    Databricks
    No answers on this topic
    IBM
    easy to follow documentation, support is there when needed
    Incentivized
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    Implementation Rating
    Databricks
    No answers on this topic
    IBM
    use saas service
    Incentivized
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    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
    Claude is better for troubleshooting actual OPS/REXX but that's not an IBM product so I understand why IBM watsonx.data isn't great for that, but if IBM watsonx.data did help with code then it would be the only product that I use.
    Incentivized
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    Scalability
    Databricks
    No answers on this topic
    IBM
    cognos integration works great
    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
    • for one automation project, we managed to cut cloud storage costs by a third through IBM watsonx.data's lakehouse optimization
    • data integration projects have had a 20 % reduction in turnaround times. Can only imagine how that will improve with the Claude partnership
    Incentivized
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    ScreenShots