starthinker VS astro

Compare starthinker vs astro and see what are their differences.

starthinker

Reference framework for building data workflows provided by Google. Accelerates authentication, logging, scheduling, and deployment of solutions using GCP. To borrow a tagline.. "The framework for professionals with deadlines." (by google)

astro

Astro SDK allows rapid and clean development of {Extract, Load, Transform} workflows using Python and SQL, powered by Apache Airflow. [Moved to: https://github.com/astronomer/astro-sdk] (by astro-projects)
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starthinker astro
1 2
166 183
- -
2.8 10.0
8 days ago over 1 year ago
Python Python
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

starthinker

Posts with mentions or reviews of starthinker. We have used some of these posts to build our list of alternatives and similar projects.
  • Connect CM360 - B=Google Big Query
    1 project | /r/adops | 31 Mar 2021
    I've used Google's StarThinker to move reports and it's quite handy, but you need some google cloud/general code experience to get it to work.

astro

Posts with mentions or reviews of astro. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-11-15.
  • After Airflow. Where next for DE?
    13 projects | /r/dataengineering | 15 Nov 2022
    What I would suggest is if you want an "Airflow 3.0" feel you check out the Astro SDK. My team and I basically spent a year and a half rewriting the Airflow DAG writing experience from the ground up. Completely different feel, highly scalable SQL/python/spark (soon) workflows that basically feel like native python. Way easier to test as well. You can pass dataframes into SQL queries, load data from any supported source to any supported warehouse, and things like lineage are natively supported :)

What are some alternatives?

When comparing starthinker and astro you can also consider the following projects:

astro-sdk - Astro SDK allows rapid and clean development of {Extract, Load, Transform} workflows using Python and SQL, powered by Apache Airflow.

Dataplane - Dataplane is a data platform that makes it easy to construct a data mesh with automated data pipelines and workflows.

airflow-maintenance-dags - A series of DAGs/Workflows to help maintain the operation of Airflow

django-q2 - A multiprocessing distributed task queue for Django. Django Q2 is a fork of Django Q. Big thanks to Ilan Steemers for starting this project. Unfortunately, development has stalled since June 2021. Django Q2 is the new updated version of Django Q, with dependencies updates, docs updates and several bug fixes. Original repository: https://github.com/Koed00/django-q

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

ComputerMonitoring_IOT - Uses Python to pull computer statistics and stores data to BigQuery using Pub/Sub, Cloud Functions.

getting-started - This repository is a getting started guide to Singer.

ad_clicker - Google Ads clicker

sqlelf - Explore ELF objects through the power of SQL

flytekit - Extensible Python SDK for developing Flyte tasks and workflows. Simple to get started and learn and highly extensible.

typhoon-orchestrator - Create elegant data pipelines and deploy to AWS Lambda or Airflow