MTSWebServices/onetl

One ETL tool to rule them all

48
/ 100
Emerging

This tool helps data engineers and analysts build and manage data pipelines to move and transform large datasets efficiently. It takes raw data from various databases and file systems like HDFS or S3, processes it using Apache Spark, and delivers cleaned, structured data to target data stores. Data professionals who regularly integrate and prepare data from disparate sources will find this valuable.

Use this if you need a flexible Python library to build batch-oriented Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) pipelines using Apache Spark.

Not ideal if you require real-time data streaming capabilities or a full-fledged data orchestration framework with built-in scheduling.

data-engineering data-integration data-warehousing big-data-processing data-pipeline-development
No Package No Dependents
Maintenance 13 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 10 / 25

How are scores calculated?

Stars

87

Forks

7

Language

Python

License

Apache-2.0

Last pushed

Mar 18, 2026

Commits (30d)

0

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