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Dataiku Data Science Studio vs KNIME comparison

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Read 16 KNIME reviews.
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Buyer's Guide
Dataiku Data Science Studio vs. KNIME
May 2022
Find out what your peers are saying about Dataiku Data Science Studio vs. KNIME and other solutions. Updated: May 2022.
610,190 professionals have used our research since 2012.
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The solution is quite stable.""Data Science Studio's data science model is very useful."

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"I was able to apply basic algorithms through just dragging and dropping.""We have found KNIME valuable when it comes to its visualization.""All of the features related to the ETL are fantastic. That includes the connectors to other programs, databases, and the meta node function.""KNIME is fast and the visualization provides a lot of clarity. It clarifies your thinking because you can see what's going on with your data.""Overall KNIME serves its purpose and does a good job.""The solution is good for teaching, since there is no need to code.""The product is open-source and therefore free to use.""From a user-friendliness perspective, it's a great tool."

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Cons
"The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective.""I think it would help if Data Science Studio added some more features and improved the data model."

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"Compared to the other data tools on the market, the user interface can be improved.""It could input more data acquisitions from other sources and it is difficult to combine with Python.""If they had a more structured training model it would be very helpful.""It's very general in terms of architecture, and as a result, it doesn't support efficient running. That is, the speed needs to be improved.""There are a lot of tools in the product and it would help if they were grouped into classes where you can select a function, rather than a specific tool.""Both RapidMiner and KNIME should be made easier to use in the field of deep learning.""From the point of view of the interface, they can do a little bit better.""Not just for KNIME, but generally for software and analyzing data, I would welcome facilities for analyzing different sorts of scale data like Likert scales, Thurstone scales, magnitude ratio scales, and Guttman scales, which I don't use myself."

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Pricing and Cost Advice
Information Not Available
  • "It's an open-source solution."
  • "The price for Knime is okay."
  • "At this time, I am using the free version of Knime."
  • "This is an open-source solution that is free to use."
  • "There is a Community Edition and paid versions available."
  • "KNIME assets are stand alone, as the solution is open source."
  • "With KNIME, you can use the desktop version free of charge as much as you like. I've yet to hit its limits. If I did, I'd have to go to the server version, and for that you have to pay. Fortunately, I don't have to at the moment."
  • "The client versions are mostly free, and we pay only for the KNIME server version. It's not a cheap solution."
  • More KNIME Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:Data Science Studio's data science model is very useful.
    Top Answer:I think it would help if Data Science Studio added some more features and improved the data model.
    Top Answer:The use case is data science, and we've deployed Data Science Studio in multiple regions for four environments: dev, preset, pre-production, and production.
    Top Answer:Overall KNIME serves its purpose and does a good job.
    Top Answer:The client versions are mostly free, and we pay only for the KNIME server version. It's not a cheap solution.
    Top Answer:KNIME can improve by adding more automation tools in the query, similar to UiPath or Blue Prism. It would make the data collection and cleanup duties more versatile.
    Ranking
    8th
    Views
    15,333
    Comparisons
    9,704
    Reviews
    2
    Average Words per Review
    433
    Rating
    9.5
    3rd
    Views
    15,880
    Comparisons
    12,080
    Reviews
    16
    Average Words per Review
    405
    Rating
    8.2
    Comparisons
    Also Known As
    Dataiku DSS
    KNIME Analytics Platform
    Learn More
    Overview

    Dataiku Data Science Studio is the collaborative data science software platform for teams of data scientists, data analysts, and engineers to explore, prototype, build, and deliver their own data products more efficiently.

    Dataiku Data Science Studio is also known as Dataiku DSS. This solution enables you to discover, share, and reuse code and applications so that you can deliver high-quality projects easily and streamline your path to production. As an enterprise leader, you can leverage the power of AI to confidently make business decisions.

    With Dataiku, an intuitive interface is guaranteed and allows users the ability to access and work with data using a point-and-click method. Dataiku analyzes the data to suggest key transformations. Beyond offering 109 data transformation capabilities, Dataiku also includes pipelines that can be generated in SQL which can thereafter be scheduled for automated recomputation.

    What's more, Dataiku allows you to create more than 20 different kinds of charts and also gives you the ability to deploy them into dashboards or create custom web applications for the use of interactive and sophisticated visualization tools.

    In addition, with Dataiku you have the option of using an in-depth statistical analysis, including but not limited to: curves fitting, univariate and bivariate analysis, principal component analysis, correlation analysis, and statistical tests.

    Dataiku Data Science Studio Consists Of:

    • Data preparation
    • Visualization
    • Machine Learning
    • Data Ops
    • ML Ops
    • Analytic Apps

    With Dataiku Data Science Studio You Can:

    • Integrate any data 10x faster
    • Build and automate sophisticated data pipelines
    • Build and share insights in minutes
    • Perform in-depth statistical analysis
    • Create thousands of models to find the best ones
    • Explore and explain models

    Dataiku Data Science Studio Benefits and Features:

    • Use your favorite languages and tools: You can create code working with tools you are already familiar with in the language you prefer (Python, R, SQL, etc.)
    • Easily reuse and share code: This feature helps you reduce inefficiencies and inconsistent data. Dataiku includes project libraries, allowing teams to centralize and share code. Although it comes pre-loaded with starter code for tasks, it also provides you with the ability to add your own code snippets.
    • Simplify complexities related to connecting to data and configuring computer resources: With this feature, data scientists can execute code in both a containerized and distributed way, while also selecting the runtime environment they want. Dataiku works to maintain those containers as well as shut them down when the job is completed.

    Features Users Find Most Valuable:

    • API
    • Reporting/Analytics
    • Third-Party Integrations
    • Data Import/Export
    • Natural Language Processing
    • Search/Filter
    • Monitoring
    • Workflow Management

    Reviews from Real Users

    IT Central Station users note that Dataiku Data Science Studio has a fantastic interface and is also flexible, intuitive, and stable. One user said "I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person." Another user mentioned “The best feature is the user interface. It allows us to see the visual flows.”

    KNIME is an open-source analytics software used for creating data science that is built on a GUI based workflow, eliminating the need to know code. The solution has an inherent modular workflow approach that documents and stores the analysis process in the same order it was conceived and implemented, while ensuring that intermediate results are always available. KNIME supports Windows, Linux, and Mac operating systems and is suitable for enterprises of all different sizes. With KNIME, you can perform functions ranging from basic I/O to data manipulations, transformations and data mining. It consolidates all the functions of the entire process into a single workflow. The solution covers all main data wrangling and machine learning techniques, and is based on visual programming.

    KNIME Features

    KNIME has many valuable key features. Some of the most useful ones include:

    • Scalability through data handling (intelligent automatic caching of data in the background while maximizing throughput performance)
    • High extensibility via a well-defined API for plugin extensions
    • Intuitive user interface
    • Import/export of workflows
    • Parallel execution on multi-core systems
    • Command line version for "headless" batch executions
    • Activity dashboard
    • Reporting & statistics
    • Third-party integrations
    • Workflow management
    • Local automation
    • Metanode linking
    • Tool blending
    • Big Data extensions

    KNIME Benefits

    There are many benefits to implementing KNIME. Some of the biggest advantages the solution offers include:

    • Integrated Deployment: KNIME’s integrated deployment moves both the selected model, and the entire data model preparation process into production simply and automatically, allowing for continuous optimization in production and also saving time because it eliminates error.
    • Elastic and Hybrid Execution: KNIME’s elastic and hybrid executions helps you reduce costs while covering periods of high demand, dynamically.
    • Metadata Mapping: KNIME enables complete metadata mapping of all aspects of your workflow. In addition, KNIME offers blueprint workflows for documenting the nodes, data sources, and libraries used, as well as runtime information.
    • Guided Analytics: KNIME’s guided analytics applications can be customized based on reusable components.
    • Powerful analytics, local automation, and workflow difference: KNIME uses advanced predictive and machine learning algorithms to provide you with the analytics you need. In combination with powerful analytics, KNIME’s automation capabilities and workflow difference prepare your organization with the tools you need to make better business decisions.
    • Supports enterprise-wide data science practices: The deployment and management functionalities of KNIME make it easy to productionize data science applications and services, and deliver usable, reliable, and reproducible insights for the business.
    • Helps you leverage insights gained from your data: Using KNIME ensures the data science process immediately reflects changing requirements or new insights.

    Reviews from Real Users

    Below are some reviews and helpful feedback written by PeerSpot users currently using the KNIME solution.

    An Emeritus Professor at a university says, “It can read many different file formats. It can very easily tidy up your data, deleting blank rows, and deleting rows where certain columns are missing. It allows you to make lots of changes internally, which you do using JavaScript to put in the conditional. It also has very good fundamental machine learning. It has decision trees, linear regression, and neural nets. It has a lot of text mining facilities as well. It's fairly fully-featured.”

    Benedikt S., CEO at SMH - Schwaiger Management Holding GmbH, explains, “All of the features related to the ETL are fantastic. That includes the connectors to other programs, databases, and the meta node function. Technical support has been extremely responsive so far. The solution has a very strong and supportive community that shares information and helps each other troubleshoot. The solution is very stable. The initial setup is pretty simple and straightforward.”

    Piotr Ś., Test Engineer at ProData Consult, says, “What I like the most is that it works almost out of the box with Random Forest and other Forest nodes.”

    Offer
    Learn more about Dataiku Data Science Studio
    Learn more about KNIME
    Sample Customers
    BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
    Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
    Top Industries
    VISITORS READING REVIEWS
    Computer Software Company23%
    Comms Service Provider13%
    Financial Services Firm13%
    Energy/Utilities Company7%
    REVIEWERS
    University28%
    Retailer22%
    Comms Service Provider11%
    Government11%
    VISITORS READING REVIEWS
    Comms Service Provider20%
    Computer Software Company17%
    Manufacturing Company9%
    Financial Services Firm9%
    Company Size
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise13%
    Large Enterprise72%
    REVIEWERS
    Small Business31%
    Midsize Enterprise29%
    Large Enterprise40%
    VISITORS READING REVIEWS
    Small Business16%
    Midsize Enterprise16%
    Large Enterprise68%
    Buyer's Guide
    Dataiku Data Science Studio vs. KNIME
    May 2022
    Find out what your peers are saying about Dataiku Data Science Studio vs. KNIME and other solutions. Updated: May 2022.
    610,190 professionals have used our research since 2012.

    Dataiku Data Science Studio is ranked 8th in Data Science Platforms with 2 reviews while KNIME is ranked 3rd in Data Science Platforms with 16 reviews. Dataiku Data Science Studio is rated 9.6, while KNIME is rated 8.2. The top reviewer of Dataiku Data Science Studio writes "Flexible and intuitive with good stability". On the other hand, the top reviewer of KNIME writes "Allows you to easily tidy up your data, make lots of changes internally, and has good machine learning". Dataiku Data Science Studio is most compared with Databricks, Alteryx, Microsoft Azure Machine Learning Studio, Amazon SageMaker and H2O.ai, whereas KNIME is most compared with Alteryx, RapidMiner, Weka, Microsoft BI and Databricks. See our Dataiku Data Science Studio vs. KNIME report.

    See our list of best Data Science Platforms vendors.

    We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.