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Autonomous Database is a cloud-based solution that uses machine learning to automate database optimization, security, backups, updates, and other routine management tasks traditionally performed by database administrators. Unlike a conventional database, an autonomous database performs all these and other tasks without human intervention.

The amount of data available to the enterprise is growing faster and faster. This increases the demand for efficient and secure database management that enhances data security, reduces downtime, improves performance, and is not prone to human error. An autonomous database can help you achieve these goals.

Types of data stored in databases

Information stored in a database management system can be highly structured (e.g., accounting records or customer information) or unstructured (e.g., digital images or spreadsheets). Data can be accessed by customers and employees directly or indirectly through enterprise software, websites or mobile applications. Additionally, many types of software—such as business analytics, customer relationship management, and supply chain applications—use information stored in databases.

Elements of an autonomous database

The standalone database consists of two key elements that are tailored to the types of workloads.

• The data warehouse performs numerous functions related to business analytics and uses data that has been previously prepared for analysis. The data warehouse environment also manages all database lifecycle operations and can scan millions of rows for queries. They can be scaled according to business needs and implemented almost on the spot.
• Transaction processing tools enable timely handling of transactional processes such as real-time data analytics, personalization and fraud detection. Transaction processing typically involves a very small number of records, relies on predefined operations, and allows simple application development and deployment.

How an autonomous database works

The autonomous database uses AI and machine learning to provide full, end-to-end automation for provisioning, security, updates, high availability, performance, change management, and error prevention.

In this regard, an autonomous database has specific characteristics.

• It’s automatic
  All database and infrastructure management, monitoring and optimization processes are automated. DBAs can now focus on more important tasks, including data aggregation, modeling, data processing and management strategies, and helping developers take advantage of the features and functions available in the database with minimal changes to the application code.
• Protects itself automatically
  Built-in security protects you from both external attacks and malicious internal users. This helps eliminate the fear of cyberattacks on unpatched or unencrypted databases.
• Self-repairs
  This can prevent downtime, including unscheduled maintenance. A standalone database may require less than 2.5 minutes of downtime per month, including patching .

The benefits of an autonomous database

An autonomous database provides several benefits:

• Maximum database uptime, performance and security – including automatic patching
• Elimination of manual, error-prone management tasks as a result of automation
• Lower costs and increase productivity by automating routine tasks

An autonomous database also allows an enterprise to redeploy its database management staff to more responsible tasks that deliver greater business value to the enterprise, such as modeling data, helping developers define data architecture, and planning future resource requirements. In some cases, an autonomous database can help a company reduce costs by reducing the number of DBAs needed to manage databases or by adapting them to more strategic tasks.

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You can read more about Autonomous Database here.

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