Spark Declarative Pipelines
PulseAugur coverage of Spark Declarative Pipelines — every cluster mentioning Spark Declarative Pipelines across labs, papers, and developer communities, ranked by signal.
1 day(s) with sentiment data
-
Data transformation: The core of data engineering and ETL
Data transformation is a crucial step in data engineering, involving the cleaning, structuring, and enrichment of raw data into usable datasets. This process enhances data quality, ensures consistency across various sou…
-
Databricks AUTO CDC enhances Spark for bitemporal history and partial updates
Databricks has enhanced its AUTO CDC feature within Apache Spark Declarative Pipelines to address complex real-world data engineering challenges. The update introduces bitemporal history tracking, which allows for the r…
-
Databricks offers framework for ETL migration via SQL, SDP, or PySpark
Databricks has introduced a new framework to help organizations migrate their existing ETL (Extract, Transform, Load) pipelines. The framework outlines three primary migration paths: utilizing Databricks SQL for SQL-hea…
-
Databricks showcases Spark Declarative Pipelines and Enzyme engine at SIGMOD 2026
Databricks is presenting its advancements in data engineering at SIGMOD 2026, focusing on Spark Declarative Pipelines (SDP) and its Enzyme engine. Enzyme, which received an honorable mention at the conference, simplifie…