Oracle recently launched its Autonomous Transaction Processing (ATP) service to complement its Autonomous Data Warehouse (ADW) offering. Similar to ADW, Oracle’s ATP service focuses on self-tuning, self-securing, and self-managing but for OLTP databases. An important part of its autonomous database strategy is its Exadata appliance, which is a scale-out optimized database system.
While Oracle has some large OLTP deployments, it often needs more administration effort compared to other databases. With Oracle ATP, Oracle raises the bar on managing OLTP databases by automating query optimization, index management, patches, security, backup, and upgrades with zero administration. Oracle leverages machine-learning capabilities to continuously monitor and learn usage and workloads and identify new query plans and indexes automatically. Oracle ATP is likely to help customers move to the cloud more quickly and help in competitive takeouts.
Forrester spoke with Aker BP, Data Intensity, Drop Tank, and Turkcell — early adopters of the Oracle autonomous database. They claim the Oracle autonomous database is a game changer, allowing them to focus on business requirements rather than deal with technology issues. Some customers claim four to five times query performance improvement with Oracle ATP after initial use.

What It Means

Machine learning and advanced software capabilities are helping to make database administration more simplified than ever. Today, several cloud database vendors offer some level of automation for OLTP databases, with more advanced capabilities on the way. Firms that invest in database automation are more likely to improve performance, scale, and security of their critical database applications. In addition, it will help lower administration costs and support new generation of applications more quickly to gain competitive advantage.