Efficient data storage is crucial for data-driven decision-making. When considering large-scale data warehousing solutions, AWS Redshift Serverless and Azure Synapse Data Warehousing stand out as powerful options. Let's explore, how data can be stored in a 10TB AWS Redshift Serverless data warehouse using the Azure Portal, contrasting it with Azure Synapse Data Warehousing. By examining the pros and cons of both solutions, we aim to empower you to make an informed choice that aligns with your data storage requirements.

import com.microsoft.spark.sqlanalytics.utils.Constants
import org.apache.spark.sql.SqlAnalyticsConnector._

val df = spark.read.
option(Constants.SERVER, "samplews.database.windows.net").
option(Constants.USER, <SQLServer Login UserName>).
option(Constants.PASSWORD, <SQLServer Login Password>).
sqlanalytics("<DBName>.<Schema>.<TableName>")

df.write.sqlanalytics("<DBName>.<Schema>.<TableName>", <TableType>)

The Azure Portal seamlessly integrates with AWS Redshift Serverless, simplifying the configuration and management of a 10TB data warehouse. Through the portal, you can easily define schemas, load data into Redshift tables, and manage the storage settings of your serverless clusters. Azure Synapse Data Warehousing offers a unified platform within the Azure ecosystem, facilitating efficient data management and analytics. The Azure Portal provides also a convenient interface for working with Redshift Serverless, delivering scalability, flexibility, and seamless data integration. Redshift Serverless eliminates the need for manual capacity planning by automatically scaling compute and storage resources. With this approach, you only pay for executed queries and data scanned, resulting in cost optimization and eliminating the overhead of managing idle clusters. Redshift Serverless offers flexibility in handling dynamic workloads, seamlessly scaling resources on-demand to accommodate data processing needs. It integrates smoothly with other AWS services like Amazon S3 and AWS Glue, creating a comprehensive and efficient data ecosystem.

Azure Synapse provides robust data warehousing capabilities within the Azure ecosystem. It integrates data warehousing, big data analytics, and data integration, offering a unified platform for data storage and processing. With dedicated SQL pools and on-demand SQL pools, Azure Synapse provides scalability to handle varying workloads. It leverages columnar storage and optimized query execution for high-performance analytics. However, direct integration with AWS Redshift Serverless may require additional steps or custom integration approaches within the Azure ecosystem.

It's important to note that Azure Synapse uses Azure Data Lake Storage Gen2 as the underlying storage platform. The cost for storing data in Azure Data Lake Storage Gen2 is based on the amount of data stored and the chosen storage redundancy options. Storing a 10TB data warehouse in Azure Synapse would cost approximately $230 per month for storage alone. This estimate does not include query running time or other processing charges. Azure Synapse Analytics offers different pricing options, including provisioned and on-demand pricing models. With provisioned pricing, you pay for dedicated SQL pool resources, while with on-demand pricing, you are charged based on the data scanned during query execution. AWS redshift supports PostGreSQL and does not have storedprocedure capability where Sysnapse use T-SQL version including Intelligent Query Processing and approximate aggregate functions

AWS Redshift Serverless may offer substantial cost savings, such as free storage. To get an accurate estimate of the cost of saving 10TB of data on AWS Redshift Serverless, consult the official AWS Redshift pricing documentation or utilize the AWS Pricing Calculator. These resources provide the most up-to-date and detailed pricing information specific to your requirements and chosen AWS region.