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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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Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Data Apps & Dashboards for Python. No JavaScript Required.
An orchestration platform for the development, production, and observation of data assets.
Incremental engine for long horizon agents 🌟 Star if you like it!
[SIGMOD'27] Easy Data Preparation with latest LLMs-based Operators and Pipelines.
Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
Python Stream Processing. A Faust fork
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.
Interactive data exploration that is extremely fast and agent-native
Turn CSV, Excel, and read-only databases into verified, editable business reports.
Declarative data quality engine. Define checks in YAML, run anywhere.
No description.
Open, audit-grade agentic data quality framework with portable industry packs
Pipeline de ingestão e busca semântica de documentos para RAG — com rate limiting, circuit breaker e fila resiliente.