Pega RPA vs PM4Py
Pega RPA
pega.comPM4Py
processintelligence.solutionsSide by side
| Figure | Pega RPA | PM4Py |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | Yes | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | — | Yes |
| Self-hosted | Yes | — |
| Plans published | 1 | 2 |
| Spec score · Process Mining Software | 7.9 (#9) | 7.8 (#13) |
| Support | Pega directs RPA users to its Support Center for questions and discussions, and says users can open a support ticket through My Support Portal for environment-specific guidance. | The commercial version includes dedicated professional support; the community version lists no support. |
Plans
In their own words
Pega RPA
Pega RPA connects software systems and automates manual work across self-hosted, web, and Windows environments. Attended automation supplies digital assistants for tedious tasks in real time, while unattended bots can run in the background 24/7 without waiting for APIs. Robot Studio provides a low-code workspace to design, test, and deploy bots; design agents map applications and generate automations. Adapters cover Windows, web, and emulator applications, including Java, SAP GUI, Chrome, Electron, and host or mainframe systems. They can automate applications without recompiling or modifying the target, including systems without a well-defined API. Robot Manager manages work queues, monitors bot performance, and enables self-healing bots. Pega describes governance, testing, and reuse, and lists connections to Pega Agentic AI, Process Mining, and Process AI. Pega Cloud controls include role-based access, SAML, OAuth, Active Directory integration, AES 256-bit encryption at rest, and TLS 1.2 and 1.3 in transit. Documentation lists R25 and 22.1.
PM4Py
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.