Apromore Process Mining vs PM4Py

Apromore Process Mining analyzes business process data so organizations can understand, monitor, and simulate their processes. It discovers process maps and BPMN models from event logs, with overlays for activity frequency and duration. Teams can filter visually, check conformance, compare processes, and examine model differences. Simulation supports current and hypothetical scenarios on BPMN models; task mining uses desktop application data to reveal routines and potential improvements or automation opportunities. Machine-learning models can predict outcomes such as SLA violations, remaining time, next activity, and case continuation. The Integration Center includes connectors for Salesforce, SAP, ServiceNow, Oracle NetSuite, and Jira, plus JDBC/ODBC access and a REST API. A no-code interface supports scheduled ETL pipelines, transformation mappings, and incremental event-log uploads. Apromore describes SaaS access for Enterprise and cloud, on-premises, or hybrid deployment for its SAP offering. Enterprise is an annual subscription with unlimited logs and process models and technical support; pricing is on request. A 30-day trial and a free version for research or education are also described.

PM4Py is a Python library for developers who want to run process mining algorithms in their own code. From event data, it can produce directly-follows graphs, Petri nets, BPMN models, and process trees. It also compares observed behavior with process models using replay and alignment-based measures. Its object-centric analysis handles event logs where events link multiple object types, such as orders, items, and deliveries. PM4Py imports and exports event logs and supports XES and OCEL 1.0 and 2.0. It can extract machine-learning features for use with pandas and scikit-learn. The free Community Version is under AGPL v3; covered work using PM4Py must be published under AGPL when distributed or made available over a network. A commercial license permits closed-source use, with pricing available by quote. Commercial evaluation without publishing code is available by requesting an evaluation license. PM4Py runs on Windows, Linux, and macOS, and pip is the recommended installation method. Graphviz must be installed and configured for visualization features.