In this article, we will discuss the significant criteria that needs to be evaluated before setting up the Enterprise Data Warehouse in Cloud with respect to Azure Synapse and Snowflake Data Cloud, and how well both the Warehouses integrate with Azure Cloud Platform.
This article only covers the qualitative measures between both the Data Warehouses across different categories that are relevant to build Enterprise Data Warehouse — Usability, Security, Integration, Monitoring, Scalability, Cluster Management, Data Management/Modelling, Cost, Data Governance, Continuous Integration & Continuous Delivery, Backup/Data Archival & Retention.
Query Performance between both the warehouses are not compared in this article. This doesn’t cover any quantitative measures between Synapse and Snowflake.
Many thanks to Arunkumar Ponnurangam for helping out in evaluating both the Cloud Data Warehouses in various aspects.All the information in this blog is relevant at the time of publishing(Feb 2021). As both warehouses release new features and frequently enhance existing features, some of the listed details may differ in the future.
Azure Synapse(formerly called SQL DW) provides a unified data platform to develop an end-to-end data pipeline. Synapse Analytics is a fully-managed service to build modern data warehouses for enterprises. Synapse Analytics brings together SQL, Apache Spark, Data Ingestion/Orchestration(Azure Data Factory), and Visualization(Power BI) into a single workspace, dramatically reducing the time to build an analytics solution.Snowflake Data CloudOne platform with a revolutionary Architecture for near-unlimited data opportunities. Snowflake’s unique architecture logically separates but natively integrates storage, computing, and services. Snowflake is designed solely for the cloud and can be hosted on any three cloud platforms(AWS, Azure, GCP) as of today.
#azure #microsoft azure synapse analytics workspace #snowflake data cloud