Winners' Circle by Raju Gulabani, VP AI, Analytics and Database, Amazon Web Services (AWS)
Nearly 8 years ago, we introduced the Amazon Relational Database Service (RDS) based on customer requests for a way to lower the cost and complexity of database management. We started with the popular MySQL open-source database, then added Oracle, SQL Server, PostgreSQL, and MariaDB engines.
Customers told us they wanted the performance and availability of commercial databases at the price of open source. This led us to build Amazon Aurora, a MySQL-compatible database that innovates on the engine and storage layers to deliver five times the performance of MySQL at one-tenth the price of commercial databases. We listened when they asked for a PostgreSQL-compatible version of Amazon Aurora, which we introduced last November. Over the life of Amazon RDS we’ve focused on making relational databases more manageable, scalable, and available. Over 90% of our roadmap is the result of feedback we receive from customers.
While customers have benefitted from our cloud-native databases and database management, they also asked for help moving their databases to the cloud, and between database engines. So we created the AWS Database Migration Service (DMS) and AWS Schema Conversion Tool, which allows them to migrate databases to AWS and between engines with virtually no downtime. Over 30,000 databases have been successfully migrated with DMS.
We’re excited to continue innovating on behalf of customers, lowering the cost of managing relational databases, providing levels of scalability and availability that have traditionally been difficult to achieve, and enabling database freedom.
Amazon Web Services