portable-data-stack-dagster
dagster-example-pipeline
| portable-data-stack-dagster | dagster-example-pipeline | |
|---|---|---|
| 1 | 1 | |
| 119 | 64 | |
| - | - | |
| 6.2 | 0.0 | |
| 27 days ago | about 2 years ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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portable-data-stack-dagster
dagster-example-pipeline
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Developing in Dagster
The associated code repo can be found here
What are some alternatives?
airflow-docker - This is my Apache Airflow Local development setup on Windows 10 WSL2/Mac using docker-compose. It will also include some sample DAGs and workflows.
mlrun - MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications.
dagster - An orchestration platform for the development, production, and observation of data assets.
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
AWS Data Wrangler - pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
jupysql - Better SQL in Jupyter. 📊
Prefect - The easiest way to build, run, and monitor data pipelines at scale.
Mage - 🧙 The modern replacement for Airflow. Mage is an open-source data pipeline tool for transforming and integrating data. https://github.com/mage-ai/mage-ai
canarypy - CanaryPy - A light and powerful canary release for Data Pipelines
superset - Apache Superset is a Data Visualization and Data Exploration Platform
aws-data-wrangler - pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL). [Moved to: https://github.com/aws/aws-sdk-pandas]