Nov 02, 2023
I'd suggest checking out the new Actable AI as well. It has a better AutoML and a lot more advanced features like Causal ML.
Altair RapidMiner and KNIME compete in the data analytics domain. KNIME appears to have the upper hand due to its comprehensive tools and resources that enhance customization and integration, justifying its cost.
Features: Altair RapidMiner provides robust data mining and machine learning tools with pre-built models, an easy-to-use interface, and strong integration with other technologies like R and Python. KNIME offers extensive workflow integrations, a rich library of extensions, and flexibility in data manipulation, being a powerful open-source platform.
Room for Improvement: Altair RapidMiner could enhance its adaptability to generative AI and address complexities in deployment. Expanding support for emerging data science tools would be beneficial. KNIME can improve by simplifying its user interface further and enhancing documentation for advanced features. Greater support for community-developed extensions would also be advantageous.
Ease of Deployment and Customer Service: KNIME offers straightforward deployment, backed by excellent training materials and a supportive community. Altair RapidMiner's deployment can be more complex, yet its dedicated assistance helps smooth the process.
Pricing and ROI: Altair RapidMiner requires a significant investment but offers an impressive ROI due to its strong data processing capabilities. KNIME, being open-source, offers low initial costs and strategic expansion potential with high returns, making it an appealing choice for flexible data solutions.
Altair RapidMiner is a leading platform for data science and machine learning, offering a user-friendly interface with powerful tools for predictive analytics. It supports integration with APIs, Python, and cloud services for streamlined workflow creation.
RapidMiner provides an efficient data science environment featuring drag-and-drop functionality, automation tools, and a wide array of algorithms, making it adaptable for novices and experts alike. Users benefit from easy data preparation and analysis alongside robust support from a vibrant community. Challenges include better onboarding and deep learning model accessibility, alongside calls for enhanced image processing and large language model integration.
What features make Altair RapidMiner stand out?Altair RapidMiner is extensively used in business and academia, facilitating tasks like predictive analytics, segmentation, and deployment. In education, it supports data science teaching and research, while in industries such as telecom, banking, and healthcare, it's used for data mining, decision trees, and market analysis.
KNIME is an open-source analytics software used for creating data science that is built on a GUI based workflow, eliminating the need to know code. The solution has an inherent modular workflow approach that documents and stores the analysis process in the same order it was conceived and implemented, while ensuring that intermediate results are always available.
KNIME supports Windows, Linux, and Mac operating systems and is suitable for enterprises of all different sizes. With KNIME, you can perform functions ranging from basic I/O to data manipulations, transformations and data mining. It consolidates all the functions of the entire process into a single workflow. The solution covers all main data wrangling and machine learning techniques, and is based on visual programming.
KNIME Features
KNIME has many valuable key features. Some of the most useful ones include:
KNIME Benefits
There are many benefits to implementing KNIME. Some of the biggest advantages the solution offers include:
Reviews from Real Users
Below are some reviews and helpful feedback written by PeerSpot users currently using the KNIME solution.
An Emeritus Professor at a university says, “It can read many different file formats. It can very easily tidy up your data, deleting blank rows, and deleting rows where certain columns are missing. It allows you to make lots of changes internally, which you do using JavaScript to put in the conditional. It also has very good fundamental machine learning. It has decision trees, linear regression, and neural nets. It has a lot of text mining facilities as well. It's fairly fully-featured.”
Benedikt S., CEO at SMH - Schwaiger Management Holding GmbH, explains, “All of the features related to the ETL are fantastic. That includes the connectors to other programs, databases, and the meta node function. Technical support has been extremely responsive so far. The solution has a very strong and supportive community that shares information and helps each other troubleshoot. The solution is very stable. The initial setup is pretty simple and straightforward.”
Piotr Ś., Test Engineer at ProData Consult, says, “What I like the most is that it works almost out of the box with Random Forest and other Forest nodes.”
We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
