Introduction
Azure Synapse Analytics, previously known as Azure SQL Data Warehouse, is a widely utilized platform for storing large volumes of data, thanks to its Massively Parallel Processing (MPP) architecture. This article aims to provide a practical approach for efficiently loading high-volume data into Synapse, leveraging parallel processing techniques, and storing the data in Synapse tables for optimal performance.
Azure Synapse is a Massively Parallel Processing (MPP) database that leverages multiple CPUs running in parallel to execute a single program. In this article, we will explore an approach for managing high-volume data in Synapse tables using dynamic partitioning techniques to