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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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ingestr is a CLI tool to copy data between any databases with a single command seamlessly.
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.
An experimental embedded SQL engine in C++20. Query Parquet, CSV, JSON, Arrow, Avro, SQLite, and Excel files directly with SQL, in-process. Early-stage.
Source-available semantic and context layer, rule engine, and semantic sidecar for agentic AI and governed analytics. Compiles declarative YAML models into optimized SQL, KPIs, and semantic context across 8 SQL dialects.
A lightweight Snowflake emulator built with Go and DuckDB for local development and testing
Turn CSV, Excel, and read-only databases into verified, editable business reports.
Reverse ETL for the code-first data stack
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.
Cold storage that queries like hot storage. High-ratio JSONL compressor with block-level random access. Query cold storage in seconds — no restore, no full decompression. 5–13% ratio on JSONL logs, 25–57% smaller than gzip. 1-hour window via DuckDB in under 6s. Free for personal and open-source use.
Open, audit-grade agentic data quality framework with portable industry packs
Data ingestion engine — Singer taps to Parquet in cloud buckets