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Awesome List
A curated list of data engineering tools for software developers
GitHub stars and default-branch commits for igorbarinov/awesome-data-engineering.
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lakeFS - Data version control for your data lake | Git for data
Open-source ETL/ELT you deploy on your own servers or cloud. Built on DuckDB: no-code/low-code visual pipelines or SQL, 385 components, dbt, CDC, data quality, reverse ETL, lineage, MCP for AI agents. No vendor cloud, no per-row billing.
Data Quality and Observability platform for the whole data lifecycle, from profiling new data sources to full automation with Data Observability. Configure data quality checks from the UI or in YAML files, let DQOps run the data quality checks daily to detect data quality issues.
Lightweight DataFrame validation decorators for Pandas, Polars, Modin, and PyArrow. No custom types required.
Declarative data quality engine. Define checks in YAML, run anywhere.
A detective for your data. Zero-config data quality monitoring — works with dbt, Postgres, BigQuery, Snowflake. No YAML.
Blazingly fast data comparison tool for Python, powered by Rust. Compare massive CSV/Parquet datasets instantly.
Open, audit-grade agentic data quality framework with portable industry packs