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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Dataiku

    Score8.6 out of 10
    N/AThe Dataiku platform unifies data work from analytics to Generative AI. It supports enterprise analytics with visual, cloud-based tooling for data preparation, visualization, and workflow automation.N/A

    IBM watsonx.ai

    Score8.8 out of 10
    N/AWatsonx.ai is part of the IBM watsonx platform that brings together new generative AI capabilities, powered by foundation models, and traditional machine learning into a studio spanning the AI lifecycle. Watsonx.ai can be used to train, validate, tune, and deploy generative AI, foundation models, and machine learning capabilities, and build AI applications with less time and data.

    $0

    Pricing
    DataikuIBM watsonx.ai
    Editions & Modules
    Discover
    Contact sales team
    Business
    Contact sales team
    Enterprise
    Contact sales team
    Free Trial
    $0
    ML functionality (20 CUH limit /month); Inferencing (50,000 tokens / month)
    Standard
    $1,050
    Monthly tier fee; additional usage based fees
    Essentials
    Contact Sales
    Usage based fees
    Offerings
    Pricing Offerings
    DataikuIBM watsonx.ai
    Free Trial
    YesYes
    Free/Freemium Version
    YesYes
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details—Pricing for watsonx.ai includes: model inference per 1000 tokens and ML tools and ML runtimes based on capacity unit hours.
    More Pricing Information
    Community Pulse
    DataikuIBM watsonx.ai
    Considered Both Products
    Dataiku
    No answer on this topic
    IBM
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    5 Answers
    98%
    Would buy again
    45 Answers
    Delivers good value for the price
    No answers on this topic
    100%
    Delivers good value for the price
    36 Answers
    Happy with the feature set
    100%
    Happy with the feature set
    5 Answers
    100%
    Happy with the feature set
    46 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    97%
    Lived up to sales and marketing promises
    30 Answers
    Implementation went as expected
    No answers on this topic
    89%
    Implementation went as expected
    33 Answers
    Features
    DataikuIBM watsonx.ai
    Platform Connectivity
    Comparison of Platform Connectivity features of Dataiku and IBM watsonx.ai
    Feature
    Dataiku
    8.6
    5 Ratings
    3% above category average
    IBM watsonx.ai
    -
    Ratings
    Connect to Multiple Data Sources8.05 Ratings00 Ratings
    Extend Existing Data Sources10.04 Ratings00 Ratings
    Automatic Data Format Detection10.05 Ratings00 Ratings
    MDM Integration6.52 Ratings00 Ratings
    Data Exploration
    Comparison of Data Exploration features of Dataiku and IBM watsonx.ai
    Feature
    Dataiku
    10.0
    5 Ratings
    18% above category average
    IBM watsonx.ai
    -
    Ratings
    Visualization10.05 Ratings00 Ratings
    Interactive Data Analysis10.05 Ratings00 Ratings
    Data Preparation
    Comparison of Data Preparation features of Dataiku and IBM watsonx.ai
    Feature
    Dataiku
    9.5
    5 Ratings
    15% above category average
    IBM watsonx.ai
    -
    Ratings
    Interactive Data Cleaning and Enrichment9.05 Ratings00 Ratings
    Data Transformations9.05 Ratings00 Ratings
    Data Encryption10.04 Ratings00 Ratings
    Built-in Processors10.04 Ratings00 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of Dataiku and IBM watsonx.ai
    Feature
    Dataiku
    8.5
    5 Ratings
    1% above category average
    IBM watsonx.ai
    -
    Ratings
    Multiple Model Development Languages and Tools8.05 Ratings00 Ratings
    Automated Machine Learning8.05 Ratings00 Ratings
    Single platform for multiple model development8.05 Ratings00 Ratings
    Self-Service Model Delivery10.04 Ratings00 Ratings
    Model Deployment
    Comparison of Model Deployment features of Dataiku and IBM watsonx.ai
    Feature
    Dataiku
    8.0
    5 Ratings
    7% below category average
    IBM watsonx.ai
    -
    Ratings
    Flexible Model Publishing Options8.05 Ratings00 Ratings
    Security, Governance, and Cost Controls8.05 Ratings00 Ratings
    AI Development
    Comparison of AI Development features of Dataiku and IBM watsonx.ai
    Feature
    Dataiku
    -
    Ratings
    IBM watsonx.ai
    6.6
    2 Ratings
    13% below category average
    Machine learning frameworks00 Ratings6.73 Ratings
    Data management00 Ratings6.43 Ratings
    Data monitoring and version control00 Ratings5.83 Ratings
    Automated model training00 Ratings6.43 Ratings
    Managed scaling00 Ratings7.03 Ratings
    Model deployment00 Ratings6.43 Ratings
    Security and compliance00 Ratings7.63 Ratings
    Best Alternatives
    DataikuIBM watsonx.ai
    Small Businesses
    RapidMiner
    Score8.9 out of 10
    Saturn Cloud
    Score7.8 out of 10
    Medium-sized Companies
    Anaconda
    Score8.8 out of 10
    DataRobot
    Score8.2 out of 10
    Enterprises
    IBM Watson Studio
    Score10 out of 10
    DataRobot
    Score8.2 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    DataikuIBM watsonx.ai
    Likelihood to Recommend
    10.0
    (4 ratings)
    9.2
    (36 ratings)
    Likelihood to Renew
    -
    (0 ratings)
    6.4
    (1 ratings)
    Usability
    10.0
    (1 ratings)
    7.7
    (6 ratings)
    Support Rating
    9.4
    (3 ratings)
    -
    (0 ratings)
    Ease of integration
    -
    (0 ratings)
    6.4
    (2 ratings)
    Product Scalability
    -
    (0 ratings)
    9.1
    (1 ratings)
    User Testimonials
    DataikuIBM watsonx.ai
    Likelihood to Recommend
    Dataiku
    Dataiku is an awesome tool for data scientists. It really makes our lives easier. It is also really good for non technical users to see and follow along with the process. I do think that people can fall into the trap of using it without any knowledge at all because so much is automated, but I dont think that is the fault of Dataiku.
    Incentivized
    Read full review
    IBM
    I have built a code accelerator tool for one of the IBM product implementation. Although there was a heavy lifting at the start to train the model on specifics of the packaged solution library and ways of working; the efficacy of the model is astounding. Having said that, watsonx.ai is very well suited for customer service automation, healthcare data analytics, financial fraud detection, and sentiment analysis kind of projects. The Watsonx.ai look and feel is little confusing but I understand over a period of time , it will improve dramatically as well. I do feel that Watsonx.ai has certain limitations from cross-platform deployment flexibility. If an organization is deeply invested in a multi-cloud environment, Watson's integration on other cloud platforms may not be seamless comported to other AI platforms.
    Incentivized
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    Pros
    Dataiku
    • Allows users to collaborate and monitor individual tasks
    • Caters to both types of analysts, coders and non-coders, alike
    • Integrate graphs and plots with visualization tools such as Tableau
    Incentivized
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    IBM
    • It allows specialists to apply several base models for specific subtasks in the field of NLP.
    • Gives the availability of many models developed for AI enhancement for different solutions.
    • Has incorporated functionality for data governance and security to support access to AI tools by multiple users.
    Incentivized
    Read full review
    Cons
    Dataiku
    • The integrated windows of frontend and backend in web applications make it cumbersome for the developer.
    • When dealing with multiple data flows, it becomes really confusing, though they have introduced a feature (Zones) to cater to this issue.
    • Bundling, exporting, and importing projects sometimes create issues related to code environment. If the code environment is not available, at least the schema of the flow we should be able to import should be.
    Incentivized
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    IBM
    • IBM watsonx.ai is expensive than other platforms.
    • Limited integraions though it has many but still some tools integrations not there for medical usecase
    • Its little difficult to learn as right now not many open reseouces
    • Community is not that strong to get any answer
    Incentivized
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    Likelihood to Renew
    Dataiku
    No answers on this topic
    IBM
    I still don't have enough experience, but i have seen a lot of demos and i have made some real world scenarios and so far so long every thing looks fine. I was at IBM Think 2025 and IBM TechXchange 2025 and the labs were really usefull and simple to understand.
    Incentivized
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    Usability
    Dataiku
    The user experience is very good. Everything feels intuitive and "flows" (sorry excuse the pun) so nicely, and the customization level is also appropriate to the tool. Even as a newer data scientist, it felt easy to use and the explanations/tutorials were very good. The documentation is also at a good level
    Incentivized
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    IBM
    I needed some time to understand the different parts of the web UI. It was slightly overwhelming in the beginning. However, after some time, it made sense, and I like the UI now. In terms of functionality, there are many useful features that make your life easy, like jumping to a section and giving me a deployment space to deploy my models easily.
    Incentivized
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    Support Rating
    Dataiku
    The open source user community is friendly, helpful, and responsive, at times even outdoing commercial software vendors. Documentation is also top notch, and usually resolves issues without the need for human interactions. Great product design, with a focus on user experience, also makes platform use intuitive, thus reducing the need for explicit support.
    Incentivized
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    IBM
    I still don't have enough experience, but i have seen a lot of demos and i have made some real world scenarios and so far so long every thing looks fine. I was at IBM Think 2025 and IBM TechXchange 2025 and the labs were really usefull and simple to understand.
    Incentivized
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    Alternatives Considered
    Dataiku
    Anaconda is mainly used by professional data scientists who have profound knowledge of Python coding, mainly used for building some new algorithm block or some optimization, then the module will be integrated into the Dataiku pipeline/workflow. While Dataiku can be used by even other kinds of users.
    Incentivized
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    IBM
    IBM watsonx.ai has been far superior to that of Chat GPT AI. the UI elements prompt responses and overall execution of the AI was much better and more accurate compared to the competition. I can not recommend using this platform enough. Great job IBM. I hope the team behind this project continues to grow and prosper.
    Incentivized
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    Scalability
    Dataiku
    No answers on this topic
    IBM
    I still don't have enough experience, but i have seen a lot of demos and i have made some real world scenarios and so far so long every thing looks fine. I was at IBM Think 2025 and IBM TechXchange 2025 and the labs were really usefull and simple to understand.
    Incentivized
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    Return on Investment
    Dataiku
    • Customer satisfaction
    • Timely project delivery
    Incentivized
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    IBM
    • Time saving to set up the infrastructure - without watsonx.ai we would have had to set up everything individually
    • The first point translates directly into cost savings
    • The compliance aspect was a game changer for us and provided us with the confidence to focus all our efforts only on IBM watsonx.ai
    Incentivized
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    ScreenShots

    IBM watsonx.ai Screenshots

    Screenshot of the foundation models available in watsonx.ai. Clients have access to IBM selected open source models from Hugging Face, as well as other third-party models, and a family of IBM-developed foundation models of different sizes and architectures.Screenshot of the Prompt Lab in watsonx.ai, where AI builders can work with foundation models and build prompts using prompt engineering techniques in watsonx.ai to support a range of Natural Language Processing (NLP) type tasks.Screenshot of the Tuning Studio in watsonx.ai, where AI builders can tune foundation models with labeled data for better performance and accuracy.Screenshot of the data science toolkit in watsonx.ai where AI builders can build machine learning models automatically with model training, development, visual modeling, and synthetic data generation.