KNIME vs Infor Birst

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.

Infor Birst is an integrated cloud-based end-to-end solution for sourcing raw data, and extracting, warehousing and reporting for enterprise data analysis. With built-in tools for data integration and strong embedded analytics capabilities, users leverage its data visualization capabilities to create and share metric-specific dashboards and reports. Users who reviewed data management said that automated data warehouse creation was a strong feature of the platform, as well as its user-friendly interface. Many users who reviewed its functionality said that, equipped with a powerful ETL and efficient ODBC drivers for integration, the platform was flexible and scalable with a multitude of features for data discovery and analysis. Around 69% of users who reviewed ease of implementation said that deployment was easy with the integrated cloud platform, though some users said that the setup processes were unclear and they required in-house IT support for onboarding. On the flip side, users who mentioned performance said that the speed of data processing and data refresh was slow and this impacted report generation capabilities. Documentation was inconsistent and often incorrect, and the use of proprietary query language made the learning curve quite steep, many users who reviewed this feature said. Support turnaround times were woefully long, even extending up to several months as reported by a number of users. Some users who reviewed functionality said that the code was buggy and the platform stalled often when processing data for ad-hoc reporting. Many users complained that these bugs were not addressed for years, and new releases often impacted pre-existing features. Possibly because of its performance issues with large amounts of data, quite a few users rate it as a good BI tool for small and midsize companies that require less complex data analysis, rather than larger enterprises. In summary, Infor Birst is a BI ecosystem with a networked approach to data visualization and predictive analytics that eliminates data silos and serves as a single source of truth for enterprise data.