Airflow Dagster - sgml/signature GitHub Wiki

Advantages/Disadvantages

task_scheduling_comparison:
  github_actions:
    primary_use_case: "CI/CD for GitHub repositories"
    workflow_definition: "YAML-based workflows"
    scheduling_mechanism: "Built-in cron scheduling (`schedule`)"
    cost_efficiency: "Free for public repos, low-cost tiers"
    integration_depth: "Deep GitHub integration"
    error_handling: "Logs in GitHub UI"
    scalability: "Optimized for CI/CD pipelines"
    best_for_cicd: true
    best_for_event_processing: false
    webhooks_support: "✅ [GitHub Webhooks](https://docs.github.com/en/developers/webhooks-and-events/webhooks)"
    license_type: "Open-source (MIT)"
    vendor_lock_in: "High—GitHub Actions is tightly coupled with GitHub repositories"
    localhost_emulation_complexity: "65%—Limited support for localhost execution, requires container-based emulation"
    localhost_dockerization: "Supports local Docker execution, but GitHub-hosted runners restrict privileged container operations."
    advantages_over_airflow: "Better suited for CI/CD workflows, simpler YAML-based configuration, native GitHub integration"
    advantages_over_step_functions_for_etl: "Limited—Not optimized for ETL workflows, lacks built-in data processing capabilities"

  circleci:
    primary_use_case: "CI/CD pipelines for multiple VCS"
    workflow_definition: "YAML-based workflows"
    scheduling_mechanism: "Cron scheduling via `triggers`"
    cost_efficiency: "Free-tier usage available"
    integration_depth: "GitHub, Bitbucket, GitLab"
    error_handling: "Debugging via CircleCI UI"
    scalability: "High concurrency for CI/CD"
    best_for_cicd: true
    best_for_event_processing: false
    webhooks_support: "✅ [CircleCI Webhooks](https://circleci.com/docs/webhooks)"
    license_type: "Proprietary (Paid Plans)"
    vendor_lock_in: "Moderate—Supports multiple VCS providers, but proprietary"
    localhost_emulation_complexity: "75%—Docker-based local execution available, but cloud-native steps may differ"
    localhost_dockerization: "Native support for local Docker execution via `circleci local execute`."
    advantages_over_airflow: "Optimized for CI/CD pipelines, easier debugging, better Git integration"
    advantages_over_step_functions_for_etl: "Limited—Not designed for complex ETL workflows, lacks built-in data transformation"

  sqs:
    primary_use_case: "Decoupled event-driven tasks"
    workflow_definition: "Queue-based task handling"
    scheduling_mechanism: "Event-driven execution"
    cost_efficiency: "Pay-per-request pricing model"
    integration_depth: "AWS services integration"
    error_handling: "Built-in DLQ (Dead Letter Queue)"
    scalability: "High-throughput message queuing"
    best_for_cicd: false
    best_for_event_processing: true
    webhooks_support: "❌ No direct webhook support"
    license_type: "Proprietary (AWS-managed)"
    vendor_lock_in: "High—Deeply integrated into AWS ecosystem"
    localhost_emulation_complexity: "40%—Partial emulation via LocalStack, lacks full AWS networking"
    localhost_dockerization: "Not applicable—SQS does not require local Docker execution."
    advantages_over_airflow: "Simpler event-driven execution, lower operational overhead, built-in retry mechanisms"
    advantages_over_step_functions_for_etl: "Moderate—Can queue messages for event-driven ETL but lacks full orchestration capabilities"

  dagster:
    primary_use_case: "Data pipeline orchestration"
    workflow_definition: "Python-native DAGs"
    scheduling_mechanism: "Cron-based scheduling (`ScheduleDefinition`)"
    cost_efficiency: "Open-source, self-hosted or managed"
    integration_depth: "Native support for dbt, Snowflake, AWS"
    error_handling: "Asset-centric lineage tracking"
    scalability: "Modular, scalable data workflows"
    best_for_cicd: false
    best_for_event_processing: true
    webhooks_support: "✅ [Dagster Webhooks](https://docs.dagster.io/concepts/partitions-schedules-sensors/sensors)"
    license_type: "Open-source (Apache 2.0)"
    vendor_lock_in: "Low—Self-hosted and open-source, flexible integrations"
    localhost_emulation_complexity: "90%—Can fully run locally, minor cloud API differences"
    localhost_dockerization: "Fully supports local Docker-based execution for development environments."
    advantages_over_airflow: "Better asset-based lineage tracking, simpler Python-native DAGs, more modular execution"
    advantages_over_step_functions_for_etl: "Limited—Focuses on batch processing rather than real-time event-driven ETL"

  aws_glue:
    primary_use_case: "ETL (Extract, Transform, Load)"
    workflow_definition: "Glue Studio visual workflows"
    scheduling_mechanism: "EventBridge-based scheduling"
    cost_efficiency: "Pay-per-use pricing model"
    integration_depth: "Deep AWS ecosystem integration"
    error_handling: "Automatic retries & logging"
    scalability: "Serverless, scalable ETL"
    best_for_cicd: false
    best_for_event_processing: true
    webhooks_support: "❌ No direct webhook support"
    license_type: "Proprietary (AWS-managed)"
    vendor_lock_in: "High—Fully dependent on AWS infrastructure"
    localhost_emulation_complexity: "30%—AWS Glue jobs require cloud execution, limited local testing"
    localhost_dockerization: "Limited—Glue jobs require AWS-managed infrastructure and cannot run directly via local Docker."
    advantages_over_airflow: "Fully managed ETL, serverless execution, deeper AWS integration"
    advantages_over_step_functions_for_etl: "High—Simpler ETL orchestration, built-in data transformations, deeper integration with AWS-native ETL tools."

docker-compose

Dagster

Bash script

Slack

+-------------------+       +-------------------+
|                   |       |                   |
|   Apache Airflow  |       |      Slack        |
|                   |       |                   |
+-------------------+       +-------------------+
        |                           |
        |                           |
        |                           |
        v                           v
+-------------------+       +-------------------+
|                   |       |                   |
|   DAG Execution   | ----> |   Slack Channel   |
|                   |       |                   |
+-------------------+       +-------------------+

Alembic initdb/createdb/upgradedb

LocalExecutor

Parallelism / Task Dependencies

Network Connections

Celery

Persistent Volumes

pip install

Permissions

Roles

XCom

Variables

Sensors

Operators

Upstream/Downstream Iteration

Logging

Providers

Schema Models

Exceptions

Testing

Concepts

Backfilling

Best Practices

Scheduler

CLI

ETL

Config

Dynamic Tasks / Task IDs

Pattern

  • Set an empty array as a global
  • Populate it using a method not bound to a task
  • Create a method that returns a PythonOperator
  • Call that method while looping through the populated array

Sample Code

Error Handling

Troubleshooting

Sample Projects

Blogs

volumes:
    airflowlogs:/usr/local/airflow/log #Add a named volume to the webserver and scheduler section of docker-compose map to fix Errno 13

Boilerplate

Email Configuration

References

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