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
Tableau Desktop
Score 8.1 out of 10
N/A
Tableau Desktop is a data visualization product from Tableau. It connects to a variety of data sources for combining disparate data sources without coding. It provides tools for discovering patterns and insights, data calculations, forecasts, and statistical summaries and visual storytelling.
$75
per month per user
Pricing
KNIME Analytics Platform
Tableau Desktop
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
Tableau
$75
per month per user
Tableau Enterprise
$115
per month per user
Offerings
Pricing Offerings
KNIME Analytics Platform
Tableau Desktop
Free Trial
No
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
All pricing plans are billed annually.
More Pricing Information
Community Pulse
KNIME Analytics Platform
Tableau Desktop
Features
KNIME Analytics Platform
Tableau Desktop
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
KNIME Analytics Platform
9.2
Ratings
10% above category average
Tableau Desktop
-
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
Tableau Desktop
-
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
Tableau Desktop
-
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
Tableau Desktop
-
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
Tableau Desktop
-
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
Tableau Desktop
8.3
Ratings
2% above category average
Pixel Perfect reports
00 Ratings
8.80 Ratings
Customizable dashboards
00 Ratings
8.40 Ratings
Report Formatting Templates
00 Ratings
7.80 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
KNIME Analytics Platform
-
Ratings
Tableau Desktop
8.7
Ratings
8% above category average
Drill-down analysis
00 Ratings
8.60 Ratings
Formatting capabilities
00 Ratings
9.20 Ratings
Integration with R or other statistical packages
00 Ratings
7.70 Ratings
Report sharing and collaboration
00 Ratings
9.20 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
KNIME Analytics Platform
-
Ratings
Tableau Desktop
8.1
Ratings
3% below category average
Publish to Web
00 Ratings
7.30 Ratings
Publish to PDF
00 Ratings
7.90 Ratings
Report Versioning
00 Ratings
8.20 Ratings
Report Delivery Scheduling
00 Ratings
9.20 Ratings
Delivery to Remote Servers
00 Ratings
8.00 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.
The best scenario is definitely to collect data from several sources and create dedicated dashboards for specific recipients. However, I miss the possibility of explaining these reports in more detail. Sometimes, we order a report, and after half a year, we don't remember the meaning of some data (I know it's our fault as an organization, but the tool could force better practices).
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
The Visualizations graphics are really good and the color options help in designing attractive charts. They help to convey more information and can be made interactive.
You can add filters with offer you to plug and play with values and understand different outcomes.
You can drag and drop options while creating charts and dashboards. also it is a very fluid layout.
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
Because right now its the best option out there (disclosure: I haven't used Qlikview or some of the other direct competitors of Tableau). The big investment is in Tableau Server not desktop. For the cost of the license of Tableau desktop, its a pretty good deal. You can hook it up to pretty much any data source easily. You can easily share the visualizations with your team/colleagues easily. Tableau Desktop is generally easy to use for business users. But the more advanced stuff is better suited for a analyst or someone with a IT/CS background.
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.
Tableau Desktop has proven to be a lifesaver in many situations. Once we've completed the initial setup, it's simple to use. It has all of the features we need to quickly and efficiently synthesize our data. Tableau Desktop has advanced capabilities to improve our company's data structure and enable self-service for our employees.
When used as a stand-alone tool, Tableau Desktop has unlimited uptime, which is always nice. When used in conjunction with Tableau Server, this tool has as much uptime as your server admins are willing to give it. All in all, I've never had an issue with Tableau's availability.
Tableau Desktop's performance is solid. You can really dig into a large dataset in the form of a spreadsheet, and it exhibits similarly good performance when accessing a moderately sized Oracle database. I noticed that with Tableau Desktop 9.3, the performance using a spreadsheet started to slow around 75K rows by about 60 columns. This was easily remedied by creating an extract and pushing it to Tableau Server, where performance went to lightning fast
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.
The Tableau Desktop's support team has been very helpful and tend to response very quickly. After all you have paid very premium price for the product and it goes to the services. This makes using the tool much easier for these who doesn't have such experience to get help quickly.
It is admittedly hard to train a group of people with disparate levels of ability coming in, but the software is so easy to use that this is not a huge problem; anyone who can follow simple instructions can catch up pretty quickly.
I think the training was good overall, but it was maybe stating the obvious things that a tech savvy young engineer would be able to pick up themselves too. However, the example work books were good and Tableau web community has helped me with many problems
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.
Time needs to be spent ahead of implementation to make sure data sources are set up and ready. Consultants need to understand the data sources and the goals before setting foot on-site. Installation is easy, learning to use it takes time. The training resources available are great.
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.
Tableau Desktop is clearly one of the best in the business. It has incredible capabilities, and many features are extremely useful. The intuitiveness of the dashboards and the graphical nature of the visualizations are widely used features and super helpful. One of the other benefits is that both programmers and non-programmers can equally explore and create their own opportunities, and seamless integration is possible.
Tableau Desktop's scaleability is really limited to the scale of your back-end data systems. If you want to pull down an extract and work quickly in-memory, in my application it scaled to a few tens of millions of rows using the in-memory engine. But it's really only limited by your back-end data store if you have or are willing to invest in an optimized SQL store or purpose-built query engine like Veritca or Netezza or something similar.
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.