Azure Synapse Analytics vs. AWS Redshift: Choosing the Best Cloud Data Warehouse
“Data is the new oil”. I know, I know — the adage is old and trite at this point. But that does not mean it is not true. The adage, I mean. In a simple world, companies across industries depend on and will continue to rely on data.
This has translated into cloud-based data warehousing solutions becoming a fundamental aspect of the successful operation of a business. Why? That would be because data warehousing solutions can help companies manage and analyze their rapidly growing data volumes.
The market offers many such solutions, yet AWS Redshift and Azure Synapse Analytics are the two best options.
Those wondering if you should look for custom services for Microsoft Azure Analytics or AWS Redshift wonder no more. In this blog, I will walk you through a quick comparative analysis between these two solutions.
What Is Referred To As AWS Redshift?
It is a fully managed petabyte-scale data warehouse service that contends with large-scale data analysis and workload reporting. Redshift utilizes a columnar storage design, optimized for analytical queries. It also gets a massively parallel processing (MPP) architecture. This translates into fast performance on enormous datasets.
What Is Referred To As Microsoft Azure Synapse Analytics?
Synapse Analytics is a unified analytics platform from tech behemoth Microsoft. It integrates and analyzes data from several sources. Consequently, this Microsoft offering becomes well-suited for various data-driven applications.
How Are AWS Redshift and Azure Synapse Analytics Different From Each Other?
● Data integration: Thanks to AWS Redshift, companies can access many data integration options. This includes Amazon S3, Amazon RDS, and various external data sources. Did I mention that batch and real-time data loading are supported? On to Azure Synapse Analytics, then. This one enables seamless integration with a variety of data sources. Besides external data sources, this list would include Azure SQL Database and Azure Data Lake Storage Gen2. It also lets you import data in real-time and in batches by the way.
● Data analytics capabilities: AWS Redshift is well-optimized for high-performance analytics. This is especially true for OLAP workloads. It is very good at handling reports and analyzing large amounts of data. Things are quite different with Azure Synapse Analytics in this regard. It provides companies with a unified analytics platform. Plus, it is sufficiently adaptable to fulfill various data analytics requirements. Synapse Analytics supports not only OLAP but also OLTP workloads.
● Data security: AWS Redshift comes equipped with vigorous data security features. The list of such features includes encryption at rest and in transit, access controls, and auditing. Redshift also ensures compliance with various industry certifications and security standards. On the other hand, with Azure Synapse Analytics, encryption, access controls, and auditing are just a few of the comprehensive data security measures offered. This one also complies with industry standards and is built on the Azure security framework.
● Machine learning support: AWS Redshift can seamlessly integrate with AWS SageMaker. This facilitates the ML model training and deployment on Redshift data. Redshift supports predictive analytics and ML based on SQL. Then there is Synapse Analytics gets ML capabilities, such as SQL-based ML and integration with Azure Machine Learning, built in right from the start. It offers an exhaustive environment for data science and ML workflows.
Final Words
No matter which of these two you pick, there is no denying that they are both high-quality data warehousing solutions, albeit with advantages and disadvantages. Synapse Analytics excels as a unified and adaptable platform for various data analytics needs, whereas AWS Redshift is terrific for high-performance analytics.
