Column level lineage for dbt
Step by step guide for column level lineage within your dbt project.
Tobiko Articles
-
-
Transpiling SQL #1: JSON Paths
Transpiling SQL is a hard problem. This blog series uses real-world transpilation challenges to explain how SQLGlot, the transpilation framework powering SQLMesh, tries to solve it.
-
Metadata everywhere!
Creating, updating, and locating project metadata is a hassle. SQLMesh makes it easier by letting models speak for themselves: inline comments automatically registered with your SQL engine.
-
Are these SQL queries the same?
How can you tell if two SQL queries are the same? Can you do better than just checking if two statements are textually equivalent?
-
SQLGlot Jumps on the Rust Bandwagon
Introducing the Rust implementation of the SQLGlot tokenizer, which significantly improves parsing performance.
-
Introducing WAP Pattern Support with Apache Iceberg
SQLMesh now supports the Write-Audit-Publish pattern when model tables are stored in the Apache Iceberg format.
-
Why Data Teams Are Adopting Declarative Pipelines
Explaining the surge in popularity of declarative data transformation while drawing some parallels with DevOps.
-
Our open source philosophy
How we're trying to build a trustworthy and thriving open source community.
-
Efficient Development with the SQLMesh Browser UI
Manually tracing DAGs and jumping between models is a drag. If you know that pain, check out the free, open source SQLMesh browser UI - it makes understanding and developing data transformation models easy.
-
Data Completeness: To Stream or Not to Stream
The tremendous push towards streaming pipelines lately has led some to believe that the days of batch processing are either over or will soon be coming to an end. But is this actually true? In this post, I explore the reasons for keeping some of your batch pipelines.