The Alteryx AI Platform gives organization automated data preparation, AI-powered analytics, and machine learning with embedded governance and security. Its self-service functionality, with self-service data prep, machine learning, and AI-generated insights, gives enterprise teams with a simplified user experience allowing everyone to create analytic solutions that improve productivity, efficiency, and the bottom line. Alteryx Designer can be used to automate every analytics step…
$4,950
per year per user (minimum of 3 users)
KNIME Analytics Platform
Score 7.8 out of 10
N/A
KNIME enables users to analyze, upskill, and scale data science without any coding. The platform that lets users blend, transform, model and visualize data, deploy and monitor analytical models, and share insights organization-wide with data apps and services.
$0
Pricing
Alteryx Platform
KNIME Analytics Platform
Editions & Modules
Designer Desktop
starting at $5,195
per year per user
Designer Cloud Professional Edition
Starting at $4,950
per year per user (minimum of 3 users)
KNIME Community Hub Personal Plan
$0
KNIME Analytics Platform
$0
KNIME Community Hub Team Plan
€99
per month 3 users
KNIME Business Hub
From €35,000
per year
Offerings
Pricing Offerings
Alteryx Platform
KNIME Analytics Platform
Free Trial
Yes
No
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Alteryx Platform
KNIME Analytics Platform
Considered Both Products
Alteryx Platform
Verified User
Anonymous
Chose Alteryx Platform
I prefer Alteryx Platform to all the above products. In my opinion, the Microsoft products (Excel, Power BI) are inferior, cheaper alternatives to Alteryx Platform.
I think Alteryx Platform offers a much more user friendly and can be owned by the business user much easier than SAS data insights tool can. Both are powerful but the end-user experience is much easier and intuitive with Alteryx compared to SAS from my perspective.
Fivetran is a basic on its own, but it is very cloud based solution and useful for large teams handling large data sets, hence wasn’t useful for our case. That is why we picked Alteryx which provides easy to use and understand interface for low knowledge, people.
I used ACL before so all my scripts were written in SQL and it was not low code at all. After me and my team started using Alteryx, we moved all the scripts to workflows in Alteryx, it took some time, but works way better than ACL, it is faster and easier to maintain it any …
Alteryx is by far the most powerful tool to carry out complex and customized calculations with ease and highly reproducible while the other tools often face memory issues and 10x more time to carry ou similar calculations
Alteryx is more efficient than competitors we've tested and used. Alteryx Designer can handle data wrangling and analysis that we once needed to do in multiple software.
I still use SQL, Python, and Excel when I have to - but alteryx has largely replaced all three of these. Every operation I need to do in any of these I can do in alteryx and see what I'm doing each step of the way - so problem solving is also easier.
IMHO KNIME is not user friendly as much as Alteryx. Learning curve is long. Regardless is Open Source, the GUI is awful. To do same job in Alteryx you need to add many components and the configuration is very complex. Although the application is free, the server side is not. I …
Digital Transformation & Innovation Lead, Middle East Africa (MEA), Turkey & Central Asia
Chose Alteryx Platform
IBM is old school, deployment capabilites and automation capabilities lack compared to many market players... Also opensource integrations were limited. Alteryx is good on both deployment and opensource integrations. New versions, IBM WatsonX, is expected to be better the but …
Microsoft Access is still in place, but will be subsitute by Alteryx, because connection to cloudbased data works, more automazitaion is possible. Easier to use.
We asked our external auditors for suggestions on how to make our processes better and they scheduled a meeting with us and presented Alteryx and then showed us a little bit about PowerBI but it was on their suggestion and their being able to show us at that presentation some …
Alteryx beats Tableau fair and square. Tableau is good for vizzy but nothing is comparable to Alteryx's data analysis and big data power. KNIME as well is nothing compared to the R&D Alteryx has. Alteryx having a cost compared to KNIME is a factor but the ROI is definitely …
Alteryx stacks up against its competitors in the marketplace because from day one its goal was to simplify and democratize data processes. Its visual nature and transparent tool set, combined with its highly addictive joy to use make it stand out from the crowd.
Alteryx is MUCH more user friendly. both provide the ability to code within them, but Alteryx has much nicer interface. The formula tools have a more simple language that is easier to learn than formulae in SSIS. Alteryx is easy to read with multi colored tools identifying what …
Alteryx low-code/no-code workflow development, and the ability to view my data at every step, immediately improved my development time by at least 60%. Highbond (formerly Galvanize / ACL) relies on a proprietary ACL script coding language, which can be time-consuming to …
Knime is open source and free. It also positions itself a little on machine learning. But the user experience and the features available are far less powerful than Alteryx. I was a former user of Lavastorm (ancestor of Infogix Data360) and got acquainted with the low-code …
Previous to Alteryx aquiring Trifacta, we looked at it as a possible compliment/replacement. WIth the aquistion, we are looking to the roadmap on full integration and are very excited. Trifacta brings a cloud native solution but currently lacks many of the features/functions …
Alteryx is a very similar product, almost all the things that are achievable in KNIME Analytics Platform can be done in Alteryx as well, but you have to pay for the Desktop version to conduct the analysis. But with KNIME Analytics Platform it is totally free and can be used …
As a commercial product Alteryx is more polished and can be even easier for a beginner, but KNIME beats Alteryx in functionality and performance. Dataiku takes the integration with Python and Git further than KNIME but isn't at the level of Alteryx and KNIME with its No …
There are two aspects which put KNIME Analytics Platform ahead of other products. Firstly the fact that KNIME Analytics Platform comes at no cost and no restrictions on its use is an instant winner for any organisation wanting to democratise their data. It means that a client …
Our organization also reviewed the Alteryx platform. From our experience KNIME had more functionality, was more stable, responsive, had more features, and was overall a better product from our experience. Alteryx is also a paid product, while KNIME is free.
Alteryx : allows for generally "data" knowledgeable workers to easily implement and develop a data model in an automated fashion. The collaboration tools built in also make is easy for members to share work, best practices, and custom modules
Having used both the Alteryx and [KNIME Analytics] I can definitely feel the ease of using the software of alteryx. The [KNIME Analytics] on the other hand isn't that great but is 90% of what alteryx can do along with how much ease it can do. Having said that, the 90% …
Knime is a more flexible option in some ways, allowing for more data manipulation if you can find the right node. It is not as scaleable in some cases, and some tasks are just easier and faster on SQL databases. It does not build charts or reports as easily as a Tableau and …
Data Scientist - Biotech Data Science Digtialization (BDSD)
Chose KNIME Analytics Platform
KNIME Analytics Platform has a nice visualization comparing to Azure Machine Learning Studio. KNIME also has a good amount of built-in preprocessing nodes and ML training nodes that makes it easier to develop workflow instead of writing codes. However this also limits the …
KNIME is a lower price point and has strong cross platform capabilities. Other platforms are locked to a specific operating system and cost in some cases substantially more, making them less good choices for smaller businesses that still need basic data unification. The fact …
Comparing the KNIME Analytics Platform to Anaconda and MATLAB, KNIME Analytics Platform's upsides are ease of use thanks to graphical interface and intuitiveness, no requirement of programming/coding and pre-existing nodes. Anybody can use it and create models even though …
We need to use SAS/STAT package within SAS to use the advanced statistical functions, but KNIME has inbuilt libraries for the same. Also, the integration with Open source (Python, R, Java codes) allows better scalability & more availability of skilled resources to work upon.
Knime is much more user simple than any high-level programming language. The ability to connect nodes ad produces outputs in minutes is a large benefit for this program
We're trying right now to get more people using it at our company so we can send management documented cases for how we can expand and purchase Alteryx Server which will extend the capabilities even more and across more departments. It's been well suited for pretty much everything we do on a repeating schedule. It's worth the time to set up the workflows. When Treasury sends me the bank download now - I save it to a folder and run our workflows and send back 2 journal entries in .9 seconds. (yes - in less than a second it's finished running)
KNIME Analytics Platform has vastly improved our effectiveness when working with large data sets. The self documenting GUI allows analysts to focus on what they are trying to accomplish, not complex code syntax. If we were to use traditional tools, like SQL, work would take much longer and it would be more difficult to collaborate both internally and with clients. Since KNIME Analytics Platform is database oriented, some spreadsheet functions are not supported, which is as it should be. For small data sets we often use Excel vlookup and pivot tables in place of KNIME Analytics Platform. If VBA code is requried, we go to KNIME Analytics Platform as we find VBA to be unstable in Excel.
Pulling data from multiple disparate data sources.
Allows users to see the data at every step of the workflow to be able to cleanse, analyze, and optimize the data.
Provides an analytics platform that is easy for users of all levels to thrive in whether they are just starting out in their analytics journey or they have a master's degree in Data Science.
Visual programming as oppose to scripting encourages data analysts to reap deeper insights from their data
Large community contribution in extending the KNIME Analytics Platform into other areas of analytics, e.g. Text Analytics, Predictive Analytics, ML, etc.
Open source with periodic updates ensures it is equipped to deal with the most sophisticated data analytics use case
Steeper Learning Curve: Alteryx can have a steep learning curve for users who are new to the platform or have limited experience with data analytics. Enhancements to the user interface and user onboarding resources could help make the learning process more intuitive and accessible to a wider range of users.
Enhanced Data Visualization Capabilities: Alteryx offers basic data visualization capabilities, but there is room for improvement in terms of advanced visualizations and interactive dashboarding features. Adding more sophisticated chart types, interactive widgets, and customization options would enhance the data visualization capabilities within the platform.
Improved Error Handling and Debugging: Alteryx provides error handling mechanisms, but enhancing the error reporting and debugging capabilities would be beneficial. Improved error messages, better visibility into data flow, and debugging tools could help users troubleshoot and resolve issues more efficiently.
Automation - e.g. RapidMiner Studio provides a Turbo Prep function, where one can get to working on models more quickly (RapidMiner is not open source though)
KNIME does not replace a regular reporting tool - it is not meant to. However, if I have already spent some time developing a data acquisition and analytical model, it would be nice to be able to deploy, for example, a monitoring or reporting module that would process data autonomously and react accordingly.
We've developed a working partnership with Alteryx. As an enablement suite, we're continuing to innovate and deliver great products with use of Alteryx in our solutions. Alteryx use expands to our global product development teams and is in use in multiple parts of our organization. Alteryx also delivers Experian demographic content to other clients in their product offering. We're highly likely to renew, but that decision is way above my pay grade.
We are happy with Knime product and their support. Knime AP is versatile product and even can execute Python scripts if needed. It also supports R execution as well; however, it is not being used at our end
I've found that while some things might take a little longer to create, the flexibility of Alteryx allows you to perform any function needed. I haven't found a use that was not available in Alteryx yet. APIs and XMLs can be created to perform certain functions. In addition, CMD line commands can be sent using Alteryx to perform certain functions as well.
The training KNIME Analytics Platform provide helps you get to grips with a product that is already very intuitive. There is a KNIME Analytics Platform way of thinking about addressing problems, but once you understand a couple of patterns which you see again and again in your workflow it all makes sense.
I use many programs and compared to others, Alteryx virtually never goes down, freezes up or gives an application error. Over a 4 year time period that I have used this program, any of these may have happened 3 times. It is an incredibly stable program that I feel completely confident in.
Alteryx is an extremely reliable platform. If there is an error in my workflow, I feel pretty strongly it was probably my fault. The platform also handles large amounts of data very quickly and can join/match, sort, filter, calculate on that data quickly as well. One of my favorite things to build into a workflow are the messages based on data/metadata and error messages based on errors I have come across before.
Stellar, bar-none. Some of the best support folks of any vendor. The Alteryx Community is the most responsive and supportive. On the rare occasion of a release issue or bug, we've been able to get quick help to solve the core problem. Alteryx does not play the blame game. They genuinely help the users solve their issues or respond to questions
KNIME's HQ is in Europe, which makes it hard for US companies to get customer service in time and on time. Their customer service also takes on average 1 to 2 weeks to follow up with your request. KNIME's documentation is also helpful but it does not provide you all the answers you need some of the time.
1st level of trainings which I've attended in Paris was easy and I was already knowing %90, that learning could have been an e-learning instead of in-person
Very good, detailed online trainings which you can take at your own pace, and strong certifications exists, certifications are extremely detailed and hard...
There is really not much to it (the installation, that is). Once you get it installed, along with any of the add-ons (demographics, R, etc.), you are up and running almost immediately. There is really no additional setup. You can immediately begin blending data, running demographics, performing spatial queries, running predictive analysis, etc. And for many of these functions, the learning curve is quite easy.
KNIME Analytics Platform is easy to install on any Windows, Mac or Linux machine. The KNIME Server product that is currently being replaced by the KNIME Business Hub comes as multiple layers of software and it took us some time to set up the system right for stability. This was made harder by KNIME staff's deeper expertise in setting up the Server in Linux rather than Windows environment. The KNIME Business Hub promises to have a simpler architecture, although currently there is no visibility of a Windows version of the product.
I used ACL before so all my scripts were written in SQL and it was not low code at all. After me and my team started using Alteryx, we moved all the scripts to workflows in Alteryx, it took some time, but works way better than ACL, it is faster and easier to maintain it any changes have to be done.
There are two aspects which put KNIME Analytics Platform ahead of other products. Firstly the fact that KNIME Analytics Platform comes at no cost and no restrictions on its use is an instant winner for any organisation wanting to democratise their data. It means that a client is free to install it on as many machines as they wish without worrying about costs, the number of seats required or payment models or procurement negotiation. It also means that we are not building costs into our clients business. Secondly, KNIME Analytics Platform has a very comprehensive set of tools for importing/exporting data, data manipulation and data science. Some products offer analytics packages on top of their base offering at additional cost and they are still not as comprehensive as what you get with KNIME Analytics Platform for free. For some types of analysis you may require to download additional packages with KNIME Analytics Platform, but its invariably at no cost, those packages are kept out of the main download to keep the size down. Due to the easy integration with R and Python, I view KNIME Analytics Platform as also having the capabilities of those languages too. This has helped me in the past with seamlessly importing a rare filetype and using very specific models not directly available in KNIME Analytics Platform.
Individual analysts can quickly generate results using their own copy of Alteryx Designer. But using the Server and developing macros for more complex needs can be time consuming.
Error handling - allows controls to be built into workflows easily and allows them to be isolated and spat into control reports that can be easily reviewed and audited, thanks to the ability to create multiple outputs in one go.
Time-saving - saved huge amounts of time, especially when moving Excel processes into Alteryx.
Product development - allowed my firm to create products that we have been able to market and sell to clients.
It is suited for data mining or machine learning work but If we're looking for advanced stat methods such as mixed effects linear/logistics models, that needs to be run through an R node.
Thinking of our peers with an advanced visualization techniques requirement, it is a lagging product.