Scaling data operations with in-memory OLTP

Data has become the center of our universe in modern digital world. Applications are designed to store and collect more and more data. Companies are looking to integrate and analyse the data to generate insights and take actions.

Data is a precious thing and will last longer than the systems themselves ~ Tim Berners-Lee

Can an existing relational database scale with high ingestion rates, improved read performance?Database

In-Memory OLTP seems to be the direction forward. This is considering your existing technology investments. Of course if the company is open to change technology there would be more options.

Found couple of very good articles posts related to SQL Server in-memory OLTP. Looks like SQL Server 2016 has fixes to most of the issues with in-memory OLTP.

I just think it is an amazing technology and if we can use it in the right way, will definitely yield great results for your customers.

Introducing SQL Server In-Memory OLTP

The Use Cases for SQL Server 2014 In-Memory OLTP

SQL Server In-Memory OLTP Internals Overview

The Promise – and the Pitfalls – of In-Memory OLTP—and-the-pitfalls—of-in-memory-oltp/

SQL Server 2016 : In-Memory OLTP Enhancements

Speeding up Business Analytics Using In-Memory Technology

Dynamic Data Masking in SQL Server 2016

Happy Learning!


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