Declarative pipelines use the same execution engine as scripted pipelines, but they add a number of new benefits.

Data + AI Summit -- Databricks, the Data and AI company, today announced it is open-sourcing the company's core declarative ETL framework as Apache Spark™ Declarative Pipelines. This initiative ...

In addition to a declarative syntax for defining a pipeline, Spark Declarative Pipelines also supports change data capture (CDC), batch and stream logic, built in retry logic, and observability hooks.

With Apache Spark Declarative Pipelines, engineers describe what their pipeline should do using SQL or Python, and Apache Spark handles the execution.

SAN FRANCISCO, June 11, 2025 /PRNewswire/ -- Data + AI Summit -- Databricks, the Data and AI company, today announced it is open-sourcing the company's core declarative ETL framework as Apache Spark™ ...

Upsolver's declarative data pipeline approach employs automation to expedite data transformation from source to target systems.

PALO ALTO, Calif., Nov. 15, 2019 – Ascend, provider of the world’s first Autonomous Dataflow Service, today announced the general availability of Declarative Pipeline Workflows, the first and only ...

Spark Declarative Pipelines provides an easier way to define and execute data pipelines for both batch and streaming ETL workloads across any Apache Spark-supported data source, including cloud ...

Declarative definitions, automated workflow integrations, and zero downtime pipeline deployments provide speed, flexibility, and stability across data lifecycle By Ascend Nov 12, 2019 Nov 12 ...

Spark Declarative Pipelines provides an easier way to define and execute data pipelines for both batch and streaming ETL workloads across any Apache Spark-supported data source, including cloud ...