KNIME vs Oracle Advanced Analytics comparison

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Executive Summary

We performed a comparison between KNIME and Oracle Advanced Analytics based on real PeerSpot user reviews.

Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining.
To learn more, read our detailed Data Mining Report (Updated: March 2024).
765,234 professionals have used our research since 2012.
Featured Review
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 good for teaching, since there is no need to code.""All of the features related to the ETL are fantastic. That includes the connectors to other programs, databases, and the meta node function.""It can handle an unlimited amount of data, which is the advantage of using Knime.""Easy to connect with every database: We use queries from SQL, Redshift, Oracle.""I've never had any problems with stability.""It's a very powerful and simple tool to use.""Since KNIME is a no-code platform, it is easy to work with.""KNIME is easy to learn."

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"Ability to pull together multiple sources of information.""The dashboard interface is intuitive and the user is able to interact with it to receive good results from the analytic.""When needed, we will work closely with Oracle support and implement their workaround in our application."

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Cons
"Though I can use KNIME in a 64-bit platform in the lab, it's missing some features. For example, from my laptop, I can use the image reader feature of KNIME. However, in the lab, the image reader node is missing.""KNIME's documentation is not strong.""I would like to see better web scraping because every time I tried, it was not up to par, although you can use Python script.""The solution is inconvenient when it comes to wrangling data that includes multiple steps or features because each step or feature requires its own icon.""​The data visualization part is the area most in need of improvement.""I'd like something that would make it easier to connect/parse websites, although I will fully admit that I'm not as proficient in KNIME as I would like to be, so it could be I'm just missing something.""Data visualization needs improvement.""KNIME is not good at visualization."

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"There are some transactions we have not been able to find through the dashboard.""Could use some refinement getting things that are not standard cloud applications, but more customized.""The performance, scalability and queries should be addressed, as well as the data distribution of certain data techniques."

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Pricing and Cost Advice
  • "It is free of cost. It is GNU licensed."
  • "KNIME desktop is free, which is great for analytics teams. Server is well priced, depending on how much support is required."
  • "KNIME is free as a stand-alone desktop-based platform but if you want to get a KNIME server then you can find the cost on their website."
  • "The price of KNIME is quite reasonable and the designer tool can be used free of charge."
  • "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."
  • More KNIME Pricing and Cost Advice →

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    Questions from the Community
    Top Answer: I've never had any problems with stability.
    Top Answer:We're using the free academic license just locally. I went for KNIME because they have a free academic license. And to be honest, I never bothered to check the prices.
    Top Answer:In the last update, KNIME started hiding a lot of the nodes. It doesn't mean hiding, but you need to know what you're looking for. Before that, you had just a tree that you could click, and you could… more »
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    Also Known As
    KNIME Analytics Platform
    OAA
    Learn More
    Overview

    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.”

    Oracle Advanced Analytics 12c delivers parallelized in-database implementations of data mining algorithms and integration with open source R. Data analysts use Oracle Data Miner GUI and R to build and evaluate predictive models and leverage R packages and graphs. Application developers deploy Oracle Advanced Analytics models using SQL data mining functions and R. With the Oracle Advanced Analytics option, Oracle extends the Oracle Database to an sclable analytical platform that mines more data and data types, eliminates data movement, and preserves security to anticipate customer behavior, detect patterns, and deliver actionable insights. Oracle Big Data SQL adds new big data sources and Oracle R Advanced Analytics for Hadoop provides algorithms that run on Hadoop. 

    Sample Customers
    Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
    Orbitz, Marriott, SGS Life Science, Masdar, AlliantEnergy Corporation, British Standards Institute, Skybox Security, Triple PointTechnology, and Coca Cola.
    Top Industries
    REVIEWERS
    University23%
    Comms Service Provider17%
    Retailer14%
    Government9%
    VISITORS READING REVIEWS
    Manufacturing Company12%
    Financial Services Firm11%
    Computer Software Company10%
    Educational Organization8%
    VISITORS READING REVIEWS
    Government15%
    Computer Software Company13%
    University13%
    Manufacturing Company13%
    Company Size
    REVIEWERS
    Small Business29%
    Midsize Enterprise27%
    Large Enterprise45%
    VISITORS READING REVIEWS
    Small Business19%
    Midsize Enterprise14%
    Large Enterprise67%
    REVIEWERS
    Small Business67%
    Midsize Enterprise22%
    Large Enterprise11%
    VISITORS READING REVIEWS
    Small Business21%
    Midsize Enterprise13%
    Large Enterprise66%
    Buyer's Guide
    Data Mining
    March 2024
    Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining. Updated: March 2024.
    765,234 professionals have used our research since 2012.

    KNIME is ranked 1st in Data Mining with 50 reviews while Oracle Advanced Analytics is ranked 7th in Data Mining. KNIME is rated 8.2, while Oracle Advanced Analytics is rated 8.0. The top reviewer of KNIME writes "A low-code platform that reduces data mining time by linking script". On the other hand, the top reviewer of Oracle Advanced Analytics writes "Helpful technical support, but performance and queries should be addressed". KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Weka and Dataiku Data Science Studio, whereas Oracle Advanced Analytics is most compared with IBM SPSS Statistics, Weka and SAS Analytics.

    See our list of best Data Mining vendors.

    We monitor all Data Mining 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.