This repository is a curated list of open-source tools for data engineering and analytics platforms. It aims to provide a comprehensive overview of the ecosystem, covering categories from storage systems and data integration to ML/AI platforms, serving as a valuable resource for data engineers, analysts, and ML practitioners.

How It Works

The list is organized into logical categories, presenting a wide array of open-source projects within each. Each entry includes the project name and a brief description, often highlighting its primary function or key differentiator. The compilation aims to map the landscape of available tools, enabling users to discover and evaluate options for their data infrastructure needs.

Quick Start & Requirements

This is a curated list, not a software project. No installation or execution is required.

Highlighted Details

• Extensive coverage across 15+ major categories of data engineering tools.
• Includes numerous projects with "⚠️ Inactive" or "⛔️ Archived" status, providing historical context.
• Features a dedicated section for LLMOps tools, reflecting current trends.
• Highlights specific integrations and compatibility notes (e.g., PostgreSQL-compatible, Kafka API compatible).

Maintenance & Community

The list is maintained by pracdata. Further information and updates may be available on Pracdata.io.

Licensing & Compatibility

This is a list of open-source projects, each with its own license. Compatibility for commercial use or closed-source linking depends on the individual licenses of the listed tools.

Limitations & Caveats

The list includes several projects marked as inactive or archived, indicating potential maintenance issues or deprecation. The sheer volume of tools may require significant effort to evaluate for specific use cases.