Alireza Sadeghi — pracdata.io - 2024 Open Source Data Engineering Landscape - January 2024
FreeOpen Source Data Engineering Landscape 2024
FreeFree tier
About Alireza Sadeghi — pracdata.io - 2024 Open Source Data Engineering Landscape - January 2024
An article by Alireza Sadeghi presenting a curated overview of the open source data engineering landscape as of 2024, focusing on active projects relevant to data platforms and the data engineering lifecycle. The landscape excludes retired, archived, and inactive projects, and emphasizes open source tools rather than commercial SaaS offerings.
Key Features
Curated list of active open source data engineering projects
Excludes retired, archived, and abandoned projects
Focuses on data engineering lifecycle and platforms
Excludes data science, ML, and AI tools except infrastructure
Includes prominent tools and notable newcomers like OneTable
Pros & Cons
Pros
- Comprehensive overview of actively maintained open source data engineering projects
- Clear criteria for tool selection ensures relevance
- Focused solely on open source, not commercial offerings
- Authored by an experienced senior data engineer and consultant
Cons
- Subjective selection may omit some valid projects
- Not a real-time list; reflects landscape as of early 2024
- Does not include detailed comparisons or reviews of individual tools
Best For
Researching open source tools for data engineeringStaying updated on the data engineering ecosystemSelecting appropriate tools for data platform architectureUnderstanding trends in open source data infrastructure
FAQ
What is the Open Source Data Engineering Landscape?
It is a curated overview of active open source tools and frameworks relevant to data engineering, presented by Alireza Sadeghi for 2024.
How are tools selected for the landscape?
Tools are selected based on activity on GitHub, community mentions, and relevance to the data engineering lifecycle; retired, archived, or inactive projects are excluded.