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
Microsoft Power BI
Score 8.5 out of 10
N/A
Microsoft Power BI is a visualization and data discovery tool from Microsoft. It allows users to convert data into visuals and graphics, visually explore and analyze data, collaborate on interactive dashboards and reports, and scale across their organization with built-in governance and security.
N/A
Pricing
KNIME Analytics Platform
Microsoft Power BI
Editions & Modules
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
No answers on this topic
Offerings
Pricing Offerings
KNIME Analytics Platform
Microsoft Power BI
Free Trial
No
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
—
More Pricing Information
Community Pulse
KNIME Analytics Platform
Microsoft Power BI
Features
KNIME Analytics Platform
Microsoft Power BI
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
KNIME Analytics Platform
9.2
Ratings
10% above category average
Microsoft Power BI
-
Ratings
Connect to Multiple Data Sources
9.60 Ratings
00 Ratings
Extend Existing Data Sources
10.00 Ratings
00 Ratings
Automatic Data Format Detection
9.10 Ratings
00 Ratings
MDM Integration
7.90 Ratings
00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
KNIME Analytics Platform
8.1
Ratings
3% below category average
Microsoft Power BI
-
Ratings
Visualization
8.00 Ratings
00 Ratings
Interactive Data Analysis
8.10 Ratings
00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
KNIME Analytics Platform
8.3
Ratings
2% above category average
Microsoft Power BI
-
Ratings
Interactive Data Cleaning and Enrichment
9.00 Ratings
00 Ratings
Data Transformations
9.50 Ratings
00 Ratings
Data Encryption
7.40 Ratings
00 Ratings
Built-in Processors
7.40 Ratings
00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
KNIME Analytics Platform
8.0
Ratings
5% below category average
Microsoft Power BI
-
Ratings
Multiple Model Development Languages and Tools
9.50 Ratings
00 Ratings
Automated Machine Learning
8.20 Ratings
00 Ratings
Single platform for multiple model development
9.30 Ratings
00 Ratings
Self-Service Model Delivery
5.00 Ratings
00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
KNIME Analytics Platform
7.3
Ratings
16% below category average
Microsoft Power BI
-
Ratings
Flexible Model Publishing Options
8.60 Ratings
00 Ratings
Security, Governance, and Cost Controls
5.90 Ratings
00 Ratings
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
KNIME Analytics Platform
-
Ratings
Microsoft Power BI
8.8
Ratings
8% above category average
Pixel Perfect reports
00 Ratings
8.50 Ratings
Customizable dashboards
00 Ratings
10.00 Ratings
Report Formatting Templates
00 Ratings
8.00 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
KNIME Analytics Platform
-
Ratings
Microsoft Power BI
8.2
Ratings
2% above category average
Drill-down analysis
00 Ratings
7.00 Ratings
Formatting capabilities
00 Ratings
9.00 Ratings
Integration with R or other statistical packages
00 Ratings
8.00 Ratings
Report sharing and collaboration
00 Ratings
9.00 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
KNIME Analytics Platform
-
Ratings
Microsoft Power BI
8.6
Ratings
3% above category average
Publish to Web
00 Ratings
8.00 Ratings
Publish to PDF
00 Ratings
9.00 Ratings
Report Versioning
00 Ratings
9.00 Ratings
Report Delivery Scheduling
00 Ratings
8.00 Ratings
Delivery to Remote Servers
00 Ratings
9.00 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
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.
Microsoft Power BI is great for sales tracking, financial reporting, and real-time operations monitoring. It integrates data from multiple sources, creating interactive dashboards for better decision-making. However, it's less ideal for real-time big data processing, offline access, or when deep customization is needed. It works best for structured reporting but struggles with highly complex data models.
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
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 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
Microsoft Power BI is an excellent and scalable tool. It has a learning curve, but once you get past that, the sky is the limit and you can build from the most simple to the most complex dashboards. I have built everything from simple reports with only a few data points to complex reports with many pages and advanced filtering.
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.
Takes a little bit to get used to it. Not natively intuitive but fairly straight forward to pick up. Also docking it a few points because you can create a really clean, simple UI in Claude very quickly that's faster than building all of this yourself in Microsoft Power BI.
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.
It is a fantastic tool, you can do almost everything related with data and reports, it is a perfect substitutive of Power Point and Excel with a high evolution and flexibility, and also it is very friendly and easy to share. I think all companies should have Power BI (or other BI tool) in their software package and if they are in the MS Suite, for sure Power BI should be the one due to all the benefits of the MS ecosystem.
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.
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.
All others apps are enablers and Microsoft Power BI is the visual that end user sees which often adds more value to the end user to make strategic decisions from this. All are equally great but Microsoft Power BI is the end result
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.
We're still early in the adoption process at this company, but we've illustrated how bad data keeps us from being more productive. ~25% of a team's work week was dedicated to effectively cleaning up entries, but it was always seen as a normal to them.