Python RPA vs Low-Code comparison

Advantages of Python RPA vs Low-code RPA:
1. Licensing model
Low-code: Enterprise licenses ($$$) per bot/machine.
Python RPA: No commercial licenses are involved in development. Orchestration platform in SaaS model, pay as you scale with up to 50% savings.
2. Lock-in
Low-code: High lock-in. Proprietary technology. If you don’t pay the license, the bots stop working. To migrate, you need to rewrite the automations.
Python RPA: No lock-in. Open technology, pure Python code. You can rotate the robots and use them as you wish.
3. Compatibility
Low-code: Limited to Windows.
Python RPA: Compatible with Windows, Linux, Mac, containers, and serverless environments.
4. Time-to-success
Low-code: Requires multiple sessions of specific training.
Python RPA: Dev JR masters the technology in a few days and can get coding right away.
5.1. Performance of the bots
Low-code: Slow because it requires an intermediate parser.
Python RPA: 3x-15x faster. It’s pure code.
5.2. Scalability and Support
Low-code: Low. Because of licensing and technical restrictions. Support needs to open tickets (n1, n2, n3) or go to specific communities.
Python RPA: High. Elastic Computing, Ultraparallelism, affordable licensing, easy learning, and numerous open communities.
6. Orchestration / Governance
Low-code: For automations of specific types and flows.
Python RPA: Complete orchestration, for any automation in code, in any framework.
7. Knowledge Requirement
Low-code: Tool-specific. Only 100,000 professionals in the world.
Python RPA: Python only. 14 million devs. People of all professions program in Python: Finance, Marketing, HR, designers, lawyers, etc.
8. Productivity
Low-code: Always need to recreate the streams, depending on available connectors.
Python RPA: Easy code reuse, 440,000 available packages, numerous open APIs and SDKs for easy integrations, versioning control, and simplified rollback.
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Python RPA vs Low-Code comparison

Discover the advantages of combining Python RPA with Low-Code and why it's the best alternative for more complex processes.

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Licensing Model

Corporate licenses ($$$) per bot/machine.
No commercial licenses required for development. SaaS-based orchestration, pay-as-you-scale model with up to 50% savings.

Lock-in

High lock-in, proprietary technology. If the license is not renewed, bots stop working. Migration requires rewriting automations.
No lock-in, open technology, pure Python code. Bots can be switched and used freely.

Compatibility

Limited to Windows.
Compatible with Windows, Linux, Mac, containers, and serverless environments.

Learning Curve

Requires multiple specific training sessions.
Junior developers can master the technology in a few days and start coding quickly.

Bot Performance

Slow due to the need for an intermediate interpreter.
3x-15x faster as it runs pure code.

Scalability & Support

Low scalability due to technical and licensing restrictions. Support requires ticketing (N1, N2, N3) or specific community assistance.

High scalability: elastic computing, ultra-parallelism, affordable licensing, quick learning curve, and various open communities.

Orchestration/Governance

Limited to specific automation types and workflows.

Full orchestration for any code-based automation, with no framework restrictions.

Knowledge Requirement

Tool-specific knowledge, with only 100,000 professionals worldwide.

Python-based, a language with 14 million developers. Professionals from various fields use Python (Finance, Marketing, HR, Designers, Lawyers, etc.).

Productivity

Flows must be recreated depending on available connectors.

Reusable code, 440,000 available libraries, multiple open APIs and SDKs for easy integration, version control, and simplified rollback.

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