Azure Synapse vs SAS: What are the differences?

Introduction

In this article, we will explore the key differences between Azure Synapse and SAS. Both Azure Synapse and SAS are powerful data analytics platforms, but they have several distinct features and capabilities that set them apart. Let's dive into the differences between these two platforms.

1. Architecture: Azure Synapse is a cloud-based platform that provides a fully managed data integration, data warehousing, and big data analytics service. It is built on top of Azure Data Lake Storage and Azure SQL Data Warehouse. On the other hand, SAS (Statistical Analysis System) is an analytics software suite that offers a wide range of capabilities, including data management, advanced analytics, business intelligence, and predictive modeling. It can be deployed on a variety of platforms, including on-premises and in the cloud.

2. Scalability: Azure Synapse is built for massive scalability, allowing users to seamlessly scale their data storage and processing resources based on their needs. It can handle large-scale data processing and analytics workloads with ease, making it suitable for enterprises dealing with vast amounts of data. SAS, on the other hand, can also handle big data analytics but may require additional hardware resources and configuration adjustments to scale effectively.

3. Data Integration: Azure Synapse provides robust data integration capabilities, enabling users to ingest, prepare, and analyze data from various sources. It allows seamless integration with other Azure services, such as Azure Data Factory and Azure Logic Apps, to build end-to-end data pipelines. In contrast, SAS offers data integration capabilities through SAS Data Integration Studio, allowing users to extract, transform, and load data from multiple sources. However, it may not have the same level of integration with external services as Azure Synapse.

4. Analytics Capabilities: Azure Synapse offers comprehensive analytical capabilities, including data exploration, advanced analytics, machine learning, and business intelligence. It provides built-in integration with popular analytics tools like Power BI, Azure Machine Learning, and Apache Spark. SAS, on the other hand, provides a wide range of statistical and analytical functions that are geared towards data scientists and statisticians. It has a rich set of built-in analytics capabilities, making it a popular choice among data scientists.

5. Collaboration and Sharing: Azure Synapse provides collaborative features that allow multiple users to work together on data projects. It supports role-based access control, allowing users to share data, insights, and models with team members securely. SAS also offers collaboration features through SAS Viya, which enables teams to work on projects collaboratively. It provides a web-based user interface for sharing reports, dashboards, and analytics models with others.

6. Pricing Model: Azure Synapse follows a consumption-based pricing model, where users pay for the resources they consume. It offers different pricing tiers based on the level of compute and storage required. SAS also offers flexible pricing options, including subscription-based and perpetual licenses. The pricing of SAS may vary based on the specific modules and features required.

In summary, Azure Synapse is a cloud-native data analytics platform that offers scalability, data integration, and advanced analytics capabilities, with seamless integration with other Azure services. SAS, on the other hand, is a comprehensive analytics software suite that provides a wide range of statistical and analytical functions, with deployment options for on-premises and cloud environments. The choice between Azure Synapse and SAS depends on factors like scalability requirements, data integration needs, and existing analytics workflows.