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
SAS Enterprise Miner
Score 9.0 out of 10
N/A
SAS Enterprise Miner is a data science and statistical modeling solution enabling the creation of predictive and descriptive models on very large data sources across the organization.
N/A
Pricing
KNIME Analytics Platform
SAS Enterprise Miner
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
SAS Enterprise Miner
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
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More Pricing Information
Community Pulse
KNIME Analytics Platform
SAS Enterprise Miner
Features
KNIME Analytics Platform
SAS Enterprise Miner
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
KNIME Analytics Platform
9.2
Ratings
10% above category average
SAS Enterprise Miner
8.8
Ratings
5% above category average
Connect to Multiple Data Sources
9.60 Ratings
8.10 Ratings
Extend Existing Data Sources
10.00 Ratings
9.00 Ratings
Automatic Data Format Detection
9.10 Ratings
9.30 Ratings
MDM Integration
7.90 Ratings
9.00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
KNIME Analytics Platform
8.1
Ratings
3% below category average
SAS Enterprise Miner
8.1
Ratings
3% below category average
Visualization
8.00 Ratings
7.10 Ratings
Interactive Data Analysis
8.10 Ratings
9.10 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
KNIME Analytics Platform
8.3
Ratings
2% above category average
SAS Enterprise Miner
8.0
Ratings
2% below category average
Interactive Data Cleaning and Enrichment
9.00 Ratings
7.80 Ratings
Data Transformations
9.50 Ratings
8.20 Ratings
Data Encryption
7.40 Ratings
8.10 Ratings
Built-in Processors
7.40 Ratings
8.10 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
SAS Enterprise Miner
8.8
Ratings
5% above category average
Multiple Model Development Languages and Tools
9.50 Ratings
7.50 Ratings
Automated Machine Learning
8.20 Ratings
9.80 Ratings
Single platform for multiple model development
9.30 Ratings
8.50 Ratings
Self-Service Model Delivery
5.00 Ratings
9.20 Ratings
Model Deployment
Comparison of Model Deployment 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.
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.
One of the major flaws is that the tool is basically an interface to SAS/STAT code. It generates code in the background and runs it. Because of that, some errors are warning might be a little difficult to understand for users who aren't proficient with SAS code.
R integration is nice but I would like to see the possibility to integrate even more statistical models different than SAS. That would allow for better performance optimization when really required.
The light client is java based and a little heavy on the OS. It would be nice to get a web-based version of the tool instead of the java one.
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
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.
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.
I have contacted SAS twice in the past year and they have been super responsive both times. They solved my problem. I am also registered for an in-person class next month and they called today to tell me that it will be an online-only session. They apologized for the change and registered me for the online version. Super helpful!
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.
For those that are used to the SAS ecosystem, SAS Enterprise Miner is a massive move in the right direction. It makes doing analytics much more enjoyable. It is more user-friendly than Spotfire or Kinesis and seems to produce better results overall. SAS Enterprise Miner seems to be written by analysts for analysts.
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.
It has a positive ROI to our business, as our sales lead rate increased after we started recommending SAS EM.
Our business operation numbers improved after we introduced SAS EM and started using predictive analytics for our customer retention and customer chain prediction.
The statistical modelling for the risk controls in our financial department helped to reduce the related residual risk.
