KNIME vs Einstein 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.

Einstein Analytics from Salesforce is a predictive analytics BI tool that uses the power of AI and machine learning to glean insights and create visualizations and reports to drive business decisions. All users who reviewed its analytics capabilities said that it excels at augmented analytics. Many users who reviewed data visualization said that templates and dashboards are easy to customize for deep-dive data exploration. With a range of reporting options and intuitive drag-and-drop functionality, the platform empowers business users to create their own reports without needing to code. Being part of the Salesforce suite, the platform integrates well with other SF offerings, as expected, as well as with external data sources. As for the tool’s data management capabilities, some users said that ETL functions are self-contained in that they replace the need to write code, however others said that data needs to be cleansed before the ETL engine can consume it for data analysis. Commenting on the software’s functionality, around 68% of users said that it is easy to drill down into KPIs with little training in analytics, whereas some users said that the platform is sparse in terms of features and does not have the same reporting capabilities as other Salesforce tools. Mentioning the interface, a majority of users said that it is clean and interactive, though quite a few users said that they preferred the classic version to the new one. A majority of the users who reviewed pricing said that, in addition to expensive per-user licenses, other costs can quickly add up, since implementation is not easy and often requires professional vendor support. Many users who discussed setup said that the platform struggles when processing large amounts of data, and plugins are needed to process heavier data sets, which further compounds costs. Quite a few users said that the platform performs well within the Salesforce ecosystem; however, it does not have the robustness and flexibility of Tableau. Overall, Einstein Analytics is a BI tool with strong out of the box ETL and data visualization capabilities that glean deeper insights into business metrics and seems to be suited for organizations with lightweight data analysis needs or those that already implement Salesforce solutions.