Metadata-driven ETL framework — engine-unified, cloud-agnostic, batch-first.https://datacoolie.github.io/datacoolie/ https://github.com/datacoolie/datacoolieen Wed, 10 Jun 2026 09:36:40 -0000 Wed, 10 Jun 2026 09:36:40 -0000 1440 MkDocs RSS plugin - v1.19.0 None https://datacoolie.github.io/datacoolie/ DataCoolie Team Architecture Why we built a metadata-driven, AI-native ETL framework that separates pipeline intent from execution — and lets LLMs do the boilerplate. https://datacoolie.github.io/datacoolie/blog/2026/05/22/why-we-built-datacoolie/ Tue, 02 Jun 2026 07:54:28 +0000 DataCooliehttps://datacoolie.github.io/datacoolie/blog/2026/05/22/why-we-built-datacoolie/ DataCoolie Team Benchmark When should you use Polars vs Spark for ETL pipelines? We benchmark both engines with DataCoolie on identical workloads and show where each shines. https://datacoolie.github.io/datacoolie/blog/2026/05/26/polars-vs-spark-for-etl--when-to-use-which/ Tue, 02 Jun 2026 07:54:28 +0000 DataCooliehttps://datacoolie.github.io/datacoolie/blog/2026/05/26/polars-vs-spark-for-etl--when-to-use-which/ DataCoolie Team Tutorial Learn how to build cloud-agnostic data pipelines in Python that run on AWS, Azure Fabric, and Databricks without rewriting code — using metadata-driven ETL. https://datacoolie.github.io/datacoolie/blog/2026/05/28/how-to-build-cloud-agnostic-data-pipelines-in-python/ Tue, 02 Jun 2026 07:54:28 +0000 DataCooliehttps://datacoolie.github.io/datacoolie/blog/2026/05/28/how-to-build-cloud-agnostic-data-pipelines-in-python/ DataCoolie Team Tutorial Step-by-step guide to implementing SCD Type 2 (slowly changing dimensions) in Python with Delta Lake using DataCoolie's metadata-driven approach. https://datacoolie.github.io/datacoolie/blog/2026/05/29/implementing-scd-type-2-in-python-with-delta-lake/ Tue, 02 Jun 2026 07:54:28 +0000 DataCooliehttps://datacoolie.github.io/datacoolie/blog/2026/05/29/implementing-scd-type-2-in-python-with-delta-lake/ DataCoolie Team Architecture DataCoolie vs Airflow and Prefect — how an ETL execution framework differs from workflow orchestrators. When to use each, and how to run DataCoolie inside an Airflow DAG. https://datacoolie.github.io/datacoolie/blog/2026/05/30/datacoolie-vs-airflow--prefect--etl-framework-vs-orchestrator/ Tue, 02 Jun 2026 07:54:28 +0000 DataCooliehttps://datacoolie.github.io/datacoolie/blog/2026/05/30/datacoolie-vs-airflow--prefect--etl-framework-vs-orchestrator/ DataCoolie Team Architecture DataCoolie vs dbt — how a metadata-driven ETL framework compares to a SQL-first transformation tool. When to use each, key differences, and how they work together. https://datacoolie.github.io/datacoolie/blog/2026/05/30/datacoolie-vs-dbt--etl-framework-vs-sql-transforms/ Tue, 02 Jun 2026 07:54:28 +0000 DataCooliehttps://datacoolie.github.io/datacoolie/blog/2026/05/30/datacoolie-vs-dbt--etl-framework-vs-sql-transforms/ DataCoolie Team Tutorial Learn ETL basics and build your first data pipeline in Python. A beginner-friendly tutorial using DataCoolie's metadata-driven approach — no prior ETL experience needed. https://datacoolie.github.io/datacoolie/blog/2026/05/30/python-etl-tutorial-for-beginners--build-your-first-data-pipeline/ Tue, 02 Jun 2026 07:54:28 +0000 DataCooliehttps://datacoolie.github.io/datacoolie/blog/2026/05/30/python-etl-tutorial-for-beginners--build-your-first-data-pipeline/