Autonomous Transaction Processing is one of a family of cloud services built on the self-driving, self-securing, and self-repairing Oracle Autonomous Database. Autonomous Transaction Processing uses machine learning and automation to eliminate human labor, human error, and manual tuning, delivering unprecedented cost saving, security, availability, and production. Autonomous Transaction Processing supports a complex mix of high-performance transactions, reporting, batch, IoT, and machine learning in a single database, allowing much simpler application development and deployment and enabling real-time analytics, personalization, and fraud detection.
Autonomous Transaction Processing provisions mission-critical, scale-out database on Oracle Exadata Infrastructure. Automates patching, upgrades, and tuning without human intervention or downtime. Users can instantly create new autonomous databases and easily convert existing databases, dramatically reducing costs and time to market. Instantly scale compute and storage online as needed. Integrated machine-learning algorithms enable the development of applications that perform real-time predictions such as personalized shopping and fraud detection.
Autonomous Transaction Processing applies security updates online, ensuring protection from known cyber attacks. Encrypts all data, whether it’s at rest or in flight. It also prevents any administrators from snooping on sensitive application data.
Automatically protects from all types of downtime, including system failures, maintenance, user errors, and changes to the application data model.
Complete automation of database and infrastructure operations cuts administrative costs up to 80 percent. The efficiency of a self-optimizing database together with elastic pay-per-use cut runtime costs up to 90 percent.
Automatic application of the latest security updates with no downtime eliminates cyberattack vulnerabilities. Protects from all types of downtime, including system failures, maintenance, user errors, and changes to the application data model. Oracle Database Vault prevents administrators from snooping on user data.
Eliminating database maintenance allows database administrators to focus on getting more value from data. Developers become more agile by instantly creating and using databases that require no manual tuning or capacity planning. Integrated machine-learning algorithms enable the development of applications that perform real-time predictions such as personalized shopping and fraud detection.
Oracle SVP Juan Loaiza introduces Autonomous Database.
Accelerate innovation with Autonomous Database.
Oracle Master Product Manager Maria Colgan talks about how Autonomous Database frees DBAs from mundane tasks.