Delta Live Tables language references

This article has information on the programming interfaces available to implement Delta Live Tables pipelines and has links to documentation with detailed specifications and examples for each interface.

Data loading and transformations are implemented in a Delta Live Tables pipeline by queries that define streaming tables and materialized views. To implement these queries, Delta Live Tables supports SQL and Python interfaces. Because these interfaces provide equivalent functionality for most data processing use cases, pipeline developers can choose the interface that they are most comfortable with. The articles in this section are detailed references for the SQL and Python interfaces and should be used by developers as they implement pipelines in their interface of choice.

Delta Live Tables SQL language reference

For pipeline developers familiar with writing queries in SQL, Delta Live Tables has a simple but powerful SQL interface designed to support the loading and transformation of data. To learn about the details of the SQL interface, including how to define streaming tables for tasks such as loading data and materialized views for transforming data, see Delta Live Tables SQL language reference.

Delta Live Tables Python language reference

For Python developers, Delta Live Tables has a Python interface designed to support the loading and transformation of data. For tasks that require processing not supported by SQL, developers can use Python to write pipeline source code that combines Delta Live Tables queries with Python functions that implement the processing not supported by the Delta Live Tables interfaces. To learn about the Delta Live Tables Python interface, including detailed specifications for the Python functions included in the interface, see Delta Live Tables Python language reference.