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This page summarizes the projects mentioned and recommended in the original post on dev.to
Workflow Python Scheduler Workflow engine data-pipelines

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  • dagster

    An orchestration platform for the development, production, and observation of data assets.

    • Second-generation data orchestration tools like Dagster and Prefect are more focused on being data-driven. They’re able to detect the kinds of data within DAGs and improve data awareness by anticipating the actions triggered by each data type.

  • Airflow

    Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

    • First-generation data orchestration tools like Airflow are primarily focused on improving usability for data scientists with the introduction of Python support (vs previous tools that required queries to be written in JSON and YAML). This improved UI made it easier for data teams to manage their pipeline flows without getting as caught up in the process.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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