Python RPA vs Low-Code comparison

This is a discussion topic for the original post at Python RPA vs Low-Code comparison - BotCity | Python RPA | Blog

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 80% 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: Windows.

✅ Python RPA: Windows / Linux / Mac, containers, serverless

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. Performance of the bots

⛔ Low-code: Slow because it requires an intermediate parser.

✅ Python RPA: 3x-15x faster. It’s pure code.

5. 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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