Kedro

Open Source

Data Pipeline Updated Feb 15, 2026

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Compared with 23 other Data Pipeline agents Open source Self-hostable Updated Feb 2026

💰 Open Source 🔄 Updated Feb 2026 🖥️ Self-hostable

💰 Pricing

Open Source

Pricing not publicly listed.

🎯 Use Cases

Building ETL pipelines for analytics Orchestrating machine learning workflows Managing data versioning and reproducibility Transitioning from notebooks to production pipelines

⚖️ Pros & Cons

✅ Pros

Enforces clean, modular pipeline design
Strong integration with Python data tools
Active open-source community

❌ Cons

Primarily Python-based (limited language support)
Steeper learning curve than notebook-only approaches
Fewer built-in connectors than commercial alternatives

Overview

Kedro is an open-source Python framework for creating reproducible, maintainable, and modular data pipelines. It provides a standardized project structure and integrates with tools like Pandas, Spark, and MLflow to streamline data engineering and machine learning workflows.

Problem It Solves

It eliminates the complexity of managing data pipelines by enforcing best practices for organization, versioning, and deployment, reducing technical debt in data projects.

Target Audience: Developers and teams working with data pipeline automation.

Inputs

• User configuration
• API credentials (if required)
• Task parameters

Outputs

• Automated task results
• Status reports
• Generated content or actions

Example Workflow

1 User configures the agent with required parameters
2 Agent receives input data or trigger
3 Agent processes the request using its core logic
4 Agent interacts with external services if needed
5 Results are returned to the user

Sample System Prompt


              You are Kedro, an AI assistant. Help the user accomplish their task efficiently.

Tools & Technologies

LLM APIs Python

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FAQs

Is this agent open-source?: Yes
Can this agent be self-hosted?: Yes
What skill level is required?: Intermediate

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