Which Microsoft SQL Server* Use Case is Right for You?

If you’re using, or planning to use, your organizational data for advanced analytics—and who isn’t, these days?—then it’s a good idea to ask yourself if you’re getting all you can from your Microsoft SQL Server* environment. The relational database management system offers two distinct use cases:

  • Business Operations: Focused on using Microsoft SQL Server purely for operational database needs, along the lines of classic online transaction processing (OLTP).
  • Enterprise Data Warehouse: Designed for data mining, analytics and continuous optimization of business strategy and operations, along the lines of classic online analytical processing (OLAP).

Deciding which use case to adopt for a given workload can be done by assessing three key considerations:

  • Workload considerations: If the workload is primarily transactional, Business Operations would make sense; if it requires maximum flexibility, go for Enterprise Data Warehouse.
  • Processor considerations: High-frequency workloads would do best with Business Operations, while high core-count, high-memory workloads would suit Enterprise Data Warehouse.
  • Storage Considerations: Low-latency requirements will be met by Business Operations, while if high bandwidth and large capacity are also a concern, Enterprise Data Warehouse is the way to go.
Figure 1: Decision-making criteria when choosing a use case
Figure 1: Decision-making criteria when choosing a use case.

Intel has worked closely with Microsoft to develop Intel® Select Solution for Microsoft SQL Server, covering both of these use cases, so now’s a good time to assess your current and future requirements.

Let’s delve into these solutions in a little more detail.

Business Operations

As we’ve seen, the Intel® Select Solution for Microsoft SQL Server Business Operations offers optimized support for primarily transactional workloads that require high frequency processing power and low latency storage. Examples of this type of workload may be those operated by a wholesale supplier or a financial trading organization.

The reference design is available in two configurations, which offer a minimum level of high performance and capability for transaction processing. Each configuration is designed to deliver a high number of transactions per minute in a two-socket server.

Enterprise Data Warehouse

Workloads best suited to the Intel® Select Solution for Microsoft SQL Server Enterprise Data Warehouse will be those requiring maximum flexibility, high processor core count and memory, and low-latency, high-bandwidth, high-capacity storage. These include insights-driving analytics use cases such as predicting patterns in customer behavior or resource usage.

Of course, it’s entirely possible you’re aiming to take a two-pronged approach: co-locating business operations and data insights on the same platform in order to maximize analytics velocity and return on hardware investments. The Intel® Select Solution for Microsoft SQL Server Enterprise Data Warehouse is optimized for this hybrid transactional/analytical processing (HTAP) use case as well.

Technology components

The technology components of the two solutions are designed and benchmarked to deliver excellent performance for their respective workloads. The key components are:

  • Microsoft SQL Server: Turns mission-critical workloads into powerful intelligence and insight with advanced analytics
  • Intel® Xeon® Scalable processors: Transform infrastructure with high-performance and new capabilities for software-defined storage
  • Intel® Optane™ SSDs: Excellent combination of low latency, high endurance, quality of service and high throughput, optimized to break through storage bottlenecks
  • Intel® Ethernet Connections: Featuring iWARP RDMA* for high data throughput, low latency and low CPU utilization—ideal for hyperconverged infrastructures.

You can learn more about Intel® Select Solutions for Microsoft SQL Server by reading these solution briefs:

Or explore more possibilities for driving business transformation with advanced analytics at www.intel.com/analytics.

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About Ken LeTourneau

Ken LeTourneau has been with Intel for 20 years and is a Solutions Architect focused on Big Data and Artificial Intelligence. He works with leading software vendors on architectures and capabilities for Big Data solutions with a focus on analytics. He provides a unique perspective to leading IT decision makers on why AI is important for 21st century organizations, advising them on architectural best practices for deploying and optimizing their infrastructure to meet their needs. Previously, Ken served as an Engineering Manager and Build Tools Engineer in Intel's Graphics Software Development and Validation group. He got his start as an Application Developer and Application Support Specialist in Intel's Information Technology group.