Delta Live Tables (DLT) is a revolutionary framework from Databricks, designed to enable customers declaratively define and deploy reliable, maintainable, and testable data processing pipelines. It eliminates the operational burden associated with managing data processing pipelines.
Here are a few reasons why you should consider DLT for your ETL pipelines. You can:
- Set expectations to define expected data quality constraints and specify how to handle records that fail the set expectations.
- Process streaming and batch data in a single DLT pipeline.
- Use change data capture (CDC) in DLT to update tables based on changes in source data.
- Run a DLT pipeline in a workflow, and resources for the pipeline are managed and autoscaled by Databricks.
- Use SQL, Python, Scala & R to develop your DLT pipelines from a simple Databricks notebook.
Watch our demo on DLT and learn more about why you should switch your ETL pipelines, and use DLT instead. You can stop worrying about ETL pipeline dependency management, daily partition computation, checkpointing and retries, data quality checks, data governance, data discovery, backlog handling, version control, infrastructure deployment, etc., and just focus on the data transformation required for your business.
You can refer to the Delta Live Tables documentation here.