Sparkling Queries | An In-Depth Spark vs SQL for data pipelines

As more big data platforms begin to support both Spark and SQL, you might wonder which one to choose. This article aims to offer some guidance from a data engineering perspective. We'll focus on how each language supports the development of scalable data pipelines for data transformation, setting aside performance considerations for now. This topic would deserve its own separate discussion.

Read More

Previous
Previous

Laktory SparkChain - A serializable spark-based data transformations

Next
Next

Data Dimensional Modeling: A shooting star?