In this session we will introduce the managed MySQL analytics service which will be available shortly. This new in-memory analytic engine has been developed in Oracle Labs from the ground up designed for massive scalability and optimized for Oracle Cloud Infrastructure. We will present the architecture of how this engine is integrated seemlessly with MySQL and provides support for near real-time analytics. With the introduction of this capability, customers can now use MySQL for both their transaction processing and analytics needs.
In this talk I’ll present a shift from Virtualized application architecture in a startup I own (called fitness360now) to containerized architecture environment. I’ll emphasize on the ability to shift from single tier architecture to a multi-tier architecture (Web-App-DB tiers) while not having virtualization overhead/penalty. I’ll speak about how to replicate between several MySQL in containerized environment, I’ll present a better way to establish a delayed replication where replication is at least 6 hours behind the origin – in order to avoid Human errors. And I’ll present a sophisticated approach to performing backup in a containerized environment.
In this session we present some of the advanced development work we are doing for automating various aspects of MySQL service and MySQL analytics service. The infrastructure which is being developed for providing this automation is based on machine learning. We expect this to significantly improve the efficiency of our service as well as provide ease of use for customers using the MySQL and the MySQL Analytics service.
Traditionally, relational databases such as MySQL have usually required a schema to be defined before documents can, but new type of data requires a new type of schema-less structure. In This session, I will show how to use MySQL as Document Store like MongoDB and couchbase.