Sisense vs KNIME

Users appreciate how Sisense creates large datasets from constantly evolving data sources to be seamlessly streamlined into actionable data, and presented easily in the form of graphs, bar and pie charts, scattergrams, line graphs, interactive maps and many more visualization types. Regarding customer support, users praise their prompt and informative responses - from implementation to handling subsequent queries — as high quality customer service that comes neatly packaged with pricing plans. Users mention that the implementation of this solution, though easy for basic setup, can be quite demanding in terms of scripting and configuration setup, especially for advanced analytics. Non-technical users might find it challenging to set up the data objects - ElastiCubes - without strong IT support. On the front-end, dashboard customization and formatting of visualizations can be tricky as these require basic knowledge of CSS, Javascript and development. Though a large number of users find this solution to be cost-effective, smaller businesses and startups that only need a limited number of licenses might find it expensive. Overall, Sisense is a strong BI solution with strong data capabilities, and its drill-down functionality empowers users to glean insightful and actionable analytics that drive business strategy by aiding in decision-making processes. To maximize its potential, businesses may require strong IT support for implementation and formatting of visualizations. It is certainly worth considering for enterprise BI needs, if the price is right!

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.