Key Databricks Features

The Lakeflow Framework (LFF) aims to expose Lakeflow Spark Declarative Pipelines (SDP) functionality through the data flow spec — so you can configure product behavior in metadata rather than bespoke pipeline code.

These are Databricks / SDP capabilities, not LFF inventions. Where we surface something in the spec, a feature page explains what LFF exposes, how you configure it, and links to Databricks Docs for full product semantics.

Not every SDP capability has (or needs) a dedicated feature page here. We document the key areas teams configure most often through LFF; other SDP behavior may still be available via the spec or pipeline resources without its own page. For the full product picture, start with Lakeflow Spark Declarative Pipelines in Databricks Docs.

Source and target type catalogs live under Supported Sources and Targets. Data quality expectations live under Data Quality.

• Change Data Capture (CDC)
• Change Data Feed (CDF)
• Multi-Source Streaming (Flows)
• Liquid Clustering
• Materialized Views
• Schema-related Databricks Features
• Soft Deletes
• Target Catalog and Schema