sqlmesh
astro
sqlmesh | astro | |
---|---|---|
12 | 2 | |
1,296 | 183 | |
8.7% | - | |
9.9 | 10.0 | |
4 days ago | over 1 year ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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.
sqlmesh
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Launch HN: Serra (YC S23) – Open-source, Python-based dbt alternative
There is also sqlmesh (https://sqlmesh.com/). Pretty new as well. It introduces some interesting concepts. For smaller dbt projects it could be a drop-in replacement as it allows importing dbt projects.
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DBT lays off 15% of their staff
I agree with you that they don't have a competitor yet. I think https://sqlmesh.com will be that competitor in the not too distant future though.
- SQL Mesh - Auto DAG generation!!
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Data transformation tools other than DBT
SQLMesh is a new SQL templating framework that addresses some of dbt's biggest gaps (column lineage, unit testing). It's not an enterprise solution, but it's an interesting project. https://github.com/TobikoData/sqlmesh
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Semantic Understanding of SQL
It’s a part of the SQLMesh IDE: https://github.com/TobikoData/sqlmesh
- Virtual Data Environments
- Blog Post on how DoorDash used the metrics layer to scale and standardize Metrics for Experimentation
- A dbt killer is born (SQLMesh)
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SQLMesh: The future of DataOps
If you don't plan on using Airflow, you can just add a custom connection implementation using one of the existing ones as a reference.
astro
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After Airflow. Where next for DE?
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?
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
astro-sdk - Astro SDK allows rapid and clean development of {Extract, Load, Transform} workflows using Python and SQL, powered by Apache Airflow.
dbd - dbd is a database prototyping tool that enables data analysts and engineers to quickly load and transform data in SQL databases.
airflow-maintenance-dags - A series of DAGs/Workflows to help maintain the operation of Airflow
dbt-coves - CLI tool for dbt users to simplify creation of staging models (yml and sql) files
sayn - Data processing and modelling framework for automating tasks (incl. Python & SQL transformations).
getting-started - This repository is a getting started guide to Singer.
sqlelf - Explore ELF objects through the power of SQL
versatile-data-kit - One framework to develop, deploy and operate data workflows with Python and SQL.
typhoon-orchestrator - Create elegant data pipelines and deploy to AWS Lambda or Airflow