Azure SQL Database Built-In In-Memory Technologies Now Generally Available

Azure SQL Database built-in In Memory technologies are now generally available for Premium database tier which includes Premium pools. In-memory technology would help in optimizing the performance of transactional (OLTP), analytics (OLAP) as well as mixed workloads (HTAP).
Microsoft states,
“These technologies allow you to achieve phenomenal performance with Azure SQL Database – 75,000 transactions per second for order processing (11X perf gain) and reduced query execution time from 15 seconds to 0.26 (57X perf). You can also use them to reduce cost – on a P2 database obtain 9X perf gain for transactions or 10X perf gain for analytics queries by implementing In-Memory technologies, without any additional cost!”
In-Memory OLTP goes increases throughput and reduces latency for transaction processing. Scenarios like trading as well as gaming can see the performance benefits. Another common scenario as per the official blog is data ingestion from events or IoT devices. You will be able to use it to speed up the caching data load as well as temp table and table variable scenarios.
Clustered Columnstore Indexes help reduce storage footprints (up to 10X) and improve performance for reporting and analytics queries. Microsoft states that you can use it with fact tables in your data marts so as to fit more data in your database and improve performance. Use it with historical data in your operational database to archive and you will be able to query up to 10 times more data.
Non-clustered Columnstore Indexes for Hybrid Transactional and Analytical Processing (HTAP) gain real-time insights into your business by querying the operational database, without needing to run an expensive ETL process and wait for the data warehouse to be populated. The Columnstore indexes allow very fast execution of analytics queries on the OLTP database, while reducing the impact on the operational workload.
In-Memory OLTP and Columnstore can also be combined: you will be able to have a memory-optimized table with a columnstore index, which would allow you to both perform very fast transaction processing as well as run analytics queries very quickly on the same data.
Mark Freydl, solution architect, Quorum Business Solutions, states,
“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.”
For more information, you can visit the official site.