Microsoft Bolsters Performance of Microsoft’s Azure SQL Cloud Database to Accelerate Time-to-market in Businesses

FREMONT, CA: Microsoft leverages in-memory data technology to optimize the performance of Microsoft’s Azure SQL cloud database. The new technology enables faster transactions speeds and improves performance for analytics queries.  

In-memory Data Technology

An in-memory data technology is a data structure that resides entirely in RAM and is distributed across multiple servers. It improves the performance of the system as data can be read and written faster than any hard disk. The technical development further provides real-time insights in businesses for better productivity and customer service.

Latest Developments

Azure SQL’s in-memory features provide cost-efficient process to manage database workloads and can achieve up to 75000 transactions per second. The in-memory technology enables instant data ingestion from IoT devices and employs faster data loading capability inthe system. It reduces the storage footprint of the system by more than 10 times and analyzes historical data for better productivity. The Hybrid Transactional and Analytical Processing (HTAP) feature of Azure improves businesses through non-clustered Columnstore Indexes. It reduces the waiting-time for data warehouse to get populated and provides instant execution of analytics queries to optimize the performance of transactional (OLTP) database.

Columnstore Indexes

The P15 database in Columnstore Indexes enhances the performance by 58 times by reducing the query time to 0.26 seconds. The P1 database further marks query running time of 4.8 seconds compared to 27 seconds in traditional devices enabling a performance gain by 5.8 times.

“Scalable performance is critical with our IoT platform for oil and gas that must run 24/7/365.  The addition of In-Memory OLTP tables and native-compiled stored procedures on Azure SQL Database for a few key operations immediately reduced our overall DTU consumption by seventy percent.  Without in-memory tables, our growth would have required significant effort to multiple areas of the platform to maintain performance.  For data-centric services, in-memory support provides instant scale to existing applications with little to no changes outside of the database,” says Mark Freydl, Solution Architect, Quorum Business Solutions.