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Amazon SageMaker vs KNIME comparison

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13,036 views|10,496 comparisons
Knime Logo
15,787 views|12,004 comparisons
Featured Review
Use Amazon SageMaker?
Hemant Addal
Buyer's Guide
Data Science Platforms
July 2022
Find out what your peers are saying about Databricks, Alteryx, Microsoft and others in Data Science Platforms. Updated: July 2022.
620,068 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 deployment is very good, where you only need to press a few buttons."

More Amazon SageMaker Pros →

"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.""KNIME is quite scalable, which is one of the most important features that we found.""From a user-friendliness perspective, it's a great tool.""I was able to apply basic algorithms through just dragging and dropping.""We have found KNIME valuable when it comes to its visualization.""The solution is good for teaching, since there is no need to code.""The most valuable feature is the data wrangling, which is what I mainly use it for.""It's a huge tool with machine learning features as well."

More KNIME Pros →

Cons
"Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."

More Amazon SageMaker Cons →

"From the point of view of the interface, they can do a little bit better.""Both RapidMiner and KNIME should be made easier to use in the field of deep learning.""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.""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.""KNIME is not scalable.""The documentation is lacking and it could be better.""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.""I would prefer to have more connectivity."

More KNIME Cons →

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:We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It… more »
    Top Answer:Hi @PankajUrmaliya and @reviewer1318050, Can you possibly assist @Larry Desjardins ​in answering their question? Thanks.
    Top Answer:We have found KNIME valuable when it comes to its visualization.
    Top Answer:The setup for KNIME is simple. I would rate the setup a five on a scale of one to five.
    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
    9th
    Views
    13,036
    Comparisons
    10,496
    Reviews
    1
    Average Words per Review
    564
    Rating
    7.0
    4th
    Views
    15,787
    Comparisons
    12,004
    Reviews
    16
    Average Words per Review
    405
    Rating
    8.2
    Comparisons
    Also Known As
    AWS SageMaker, SageMaker
    KNIME Analytics Platform
    Learn More
    Overview

    Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.

    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 Amazon SageMaker
    Learn more about KNIME
    Sample Customers
    DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit
    Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
    Top Industries
    VISITORS READING REVIEWS
    Computer Software Company21%
    Comms Service Provider12%
    Media Company10%
    Financial Services Firm10%
    REVIEWERS
    University25%
    Retailer20%
    Comms Service Provider15%
    Government10%
    VISITORS READING REVIEWS
    Comms Service Provider21%
    Computer Software Company16%
    Manufacturing Company9%
    Financial Services Firm8%
    Company Size
    REVIEWERS
    Midsize Enterprise57%
    Large Enterprise43%
    VISITORS READING REVIEWS
    Small Business14%
    Midsize Enterprise11%
    Large Enterprise75%
    REVIEWERS
    Small Business30%
    Midsize Enterprise27%
    Large Enterprise43%
    VISITORS READING REVIEWS
    Small Business16%
    Midsize Enterprise15%
    Large Enterprise69%
    Buyer's Guide
    Data Science Platforms
    July 2022
    Find out what your peers are saying about Databricks, Alteryx, Microsoft and others in Data Science Platforms. Updated: July 2022.
    620,068 professionals have used our research since 2012.

    Amazon SageMaker is ranked 9th in Data Science Platforms with 1 review while KNIME is ranked 4th in Data Science Platforms with 15 reviews. Amazon SageMaker is rated 7.0, while KNIME is rated 8.2. The top reviewer of Amazon SageMaker writes "Good deployment and monitoring features, but the interface could use some improvement". 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". Amazon SageMaker is most compared with Databricks, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio, Domino Data Science Platform and IBM Watson Studio, whereas KNIME is most compared with Alteryx, RapidMiner, Microsoft BI, Weka and SAS Analytics.

    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.