The latest Magic Quadrant for Analytics and Business Intelligence platforms is still led by Power BI, with no mention of KNIME, which was previously included in the Data Science and Machine Learning platforms. With the new updates and features, shouldn’t they both be considered in the same report?
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@piva it is not that easy to follow all of Gartner’s various categories. Some time ago they seem to have stopped putting “Multipersona Data Science and Machine Learning Platforms” or “Market Guide for DSML Engineering Platforms” in quadrants and instead opted for doing customer review based comparisons without a specific quadrant or overall estimations.
More interesting than some external recommendations might be to do one’s own evaluation and see what product and platform will suit your needs - if that was the question implied 
Another interesting aspect might be KNIME’s placement on the well known “MAD (Machine Learning, Artificial Intelligence & Data) Landscape” by Matt Turck.
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@mlauber71, it’s not just a matter of conducting one’s own evaluation, but also of supporting those evaluations to convince customers. In this regard, Magic Quadrants are definitely a point of reference, and it’s worth making an effort to consider all of Gartner’s different categories to facilitate comparisons with competitors.
I rather consider KNIME an ETL and Data Science Tool not a BI Tool like Power BI or Tableau which focus on Data Visualization. But that is just my personal opinion. Gartner certainly does not care to much what I think 
br
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Found this article: Alteryx: The Analytics Platform Landscape (NYSE:AYX) | Seeking Alpha
If you Ctrl + F for KNIME, you will find a possible reason why KNIME has been declining gradually on the Gartner Magic Quadrant.
In my opinion, KNIME offers something revolutionary. It does not fit into any existing companies’ patterns and therefore it is a bit of an outlier, kind of like WordPress before it took over the majority of Website CMS market.
When I introduced KNIME to a co-worker, she sighed and made a comment: “Another software we spend our money on…” and I can respond to that: “No it’s free”. We are still mooching over here, but I keep trying to advocate for KNIME Hub especially to replace our IBM Cognos installation.
In contrast to KNIME, in order to match Microsoft, IBM is increasing its user license cost to match Microsoft’s without improving its Cognos product. That sounds like a good way to improve one’s standing on Gartner’s Magic Quadrant.
KNIME is a game changer and it’s our responsibility to help it grow in its own way. I think KNIME shouldn’t try to fit Gartner’s mold in defining its future.
All above is just my personal take.
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Just to be clear: there is no Magic Quadrant any more that features either KNIME or Alteryx (the last one was in 2021). As I mentioned they changed their system
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With the growing demand for analytics and BI tools in small and medium enterprises, the low code approach should be more appealing than pricing alone, particularly when comparing KNIME and Power BI. Both tools offer a free desktop version and commercial cloud services.
In my opinion, Power BI’s advanced visualization functionalities and the availability of free or low-cost dashboards for various use cases make it more appealing to beginner customers, compared to the technical focus found in a large part of KNIME’s documentation.
Considering the increasing availability of ETL functionalities in Power BI and the integration of advanced data modeling in Azure, KNIME doesn’t appear to be a significant competitor to Microsoft for new companies: having the support of a report like the one from Gartner would greatly assist in simplifying this comparison.
@piva, I use both KNIME and Power BI. Many of my KNIME programs have Send to Power BI nodes so that their visualizations will be handled by Power BI. I don’t think you should limit yourself to choosing Power BI over KNIME or vice versa. Since KNIME is free, you basically have nothing preventing you from using it. If your organization prevents you from installing it, you can download it as a zip file, extract it into your Downloads folder, and run it from there.
In my opinion:
Working with KNIME is easier than Microsoft’s DAX
KNIME can work with many more data sources than Microsoft
KNIME does not lock me in. If I decide to migrate, I can do so in my own time. KNIME will still be available on my desktops to run my existing processes
KNIME is not a significant competitor of Microsoft, but it doesn’t need to be one. Instead, it needs to work well with Microsoft.
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Hi @atiorile ,
Same here.
While this integration can be beneficial for those who are already familiar with both tools, for a new user, adopting two tools can be cumbersome and something they would prefer to avoid.
Indeed, the purpose of this thread is to seek an independent and comprehensive evaluation of BI tools, allowing customers to make informed decisions.
BR, Pietro
There is no need to choose - you can have it all 
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Hi @piva,
I agree with @mlauber71. When pitching about KNIME, I always use that line: “No need to choose - you can have it all”
On KNIME, annotations can also be added, containing step-by-step instructions to run the workflow. This makes it very easy for beginner users to run their first workflows.
I feel like beginner users often have their blinders on and choose whatever that is only one step away from Microsoft Excel, like Power Query, then Power BI, then Dataflow, then suddenly you fall to Microsoft’s trap and have to pay for OneLake, Fabric, Synapse, Data Factory, etc.
The decision makers should also not trust Gartner blindly. Each organization is not a cookie cutter org that fits whatever criterias determined by Gartner. Having said that, if KNIME is a leader on the Gartner magic quadrant, I’d definitely pull it out from my pocket and wave it to everyone. I’m just an opportunist that way. I don’t want KNIME to change to fit Gartner’s mold though.
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I fear the options of influencing Gartner are limited. What one can do is write a positive entry though. They switched to this user review and comparison system for several tools without giving explicit recommendations (or things that might be interpreted as such).
KNIME I think has done some things to help people make decisions about data platforms.
KNIME still is not a household name and even a lot of people in the data analytics profession have not heard of it or just prefer to do everything in code - sometimes I wonder if this is also preserve some of the myths of fancy AI stuff. On the other hand like mentioned in the article you linked it is happening that some companies are shifting their focus more to cloud services. And while KNIME also does work well with clouds it might then not be the first choice as a tool. So there is room for improvement and convincing.
I am looking forward to ne new version 5.0 which might help to make KNIME easier to handle for beginners. On the other hand there is the question if the current popularity of low-code will indeed lead companies to adopt something like a citizen data scientist approach which would well be served by a spread of KNIME in a company or rely on specialists and cloud and outsourcing (offshoring) analytic capabilities. The jury is still out on that …
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To avoid this, a comprehensive report like the Magic Quadrant for Integration Platforms would provide customers with the necessary information to make informed decisions among different approaches and vendors.
While it’s important for decision-makers to exercise caution and not solely rely on Gartner’s reports, the inclusion of reputable companies in their analyses allows for the rejection of the analysis if they disagree with the results. On the other hand, Gartner’s reputation is at stake when publishing such reports.
Indeed, the decision-making process is not as simple as making a binary choice between good and bad. Different tools may be suitable for different applications and contexts. In my experience, companies transitioning from data silos and office-based tools to more structured analytics approaches are often seeking data modeling and reporting tools: drag-and-drop workflows may not align with their immediate needs.
Having an analysis of a solution’s strategy and how it compares to other solutions is essential for making decisions that align with individual needs.
Drag and drop workflows will be very useful in dealing with inefficient data models scattered throughout various legacy systems. KNIME has been a life saver for me in a project like this with a data warehouse project that keeps getting delayed. For a company with the right size, one may argue that KNIME Hub can be a reasonable investment at least as a stop gap until the implementation of a data warehouse project. Long term commitments always start with a small one.
Reporting Tools offer great visualizations, but they often leave a lot to be desired when it comes to data manipulation capabilities. For example, IBM Cognos (A Gartner MQ Visionary) can not handle further complex processing like looping through data, pivoting/unpivoting an intermediate query (not the final result). With KNIME I feel like there is no limit on the amount of data manipulation I can do. I can even tell the workflow to run processes in parallel.
So there is no problem in allowing someone to assess the functionalities of KNIME by comparing it with other tools in the same field of application, such as in the case of the Magic Quadrant, which is my initial request for this thread.
There is no problem in allowing someone to compare KNIME functionalities with other tools. I have done it myself by comparing it with other ETL tools and other data manipulation and reporting tools. You have used KNIME. So, you know that it can be downloaded as zip or an install file. When it comes to KNIME Hub, you can request a demo through Demo page | KNIME
I would recommend taking Gartner Magic Quadrant with a grain of salt and ensure that you do your own due diligence. I’m not a KNIME staff. So, I don’t know if they are blocking Gartner from reviewing KNIME.
Again: there is no magic quadrant any more (like until 2021) for these tools but collections of reviews by users which can be used to provide comparisons between tools. So everyone can use these comparisons and read them. With KNIME one can also just give it a try (for free) or read the material about what would constitute a suitable platform - where unsurprisingly KNIME would be a match but the criteria can be used to evaluate other platforms.
@piva maybe you have ideas or material what would be important features and concepts you would like in an analytics platform.
2023 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms has been released on April 5 2023
The capabilities analyzed for the report are:
- Automated insights
- Analytics catalog
- Data preparation
- Data source connectivity
- Data storytelling
- Data visualization
- Governance
- Natural language query
- Reporting
- Data science integration
- Metrics store
- Collaboration
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