KNIME vs Pyramid Analytics

KNIME is a robust open-source solution with cross-platform interoperability. It integrates with a range of software, such as JS, R, Python and Spark. With a variety of nodes and functions, it can process large datasets with a decent level of control in each step. Workflows are displayed as connected nodes, making it easy to isolate and fix specific steps. It also contains built-in tools to create and test supervised and unsupervised machine learning models. Users found the UI very intuitive and flexible. On the flip side, they found the tool visually lacking and primitive. The system also has performance and stability issues. Processing big data is very time consuming since the platform isn’t cloud-based. Users reported excessive memory usage as well. It also lacks reporting or monitoring features. Decent technical knowledge is required to fully leverage its capabilities.

Pyramid Analytics is a flexible, scalable BI platform with machine learning capabilities. It lets users mash up data from multiple sources, model data within the application and run reports in mere minutes, as opposed to manual processes that would take hours.Its numerous features have the ability to carry out complex data analysis. Users found customer support to be helpful when demonstrating the tool’s full potential. Users also liked the ability to incorporate AI into their dashboards. However, Some users found navigating through dashboards to be difficult. Users also complained that dashboard features could be more effective. New features were sometimes unstable, introducing bugs to existing functionality. Conclusively, it is a cost-effective, intuitive solution with excellent support that can quickly deliver insights to all levels of a businesses.