Reviewing use cases for ADB

Customers who want a highly performant database service capable of automatically managing life cycle operations would use ADB. Things to remember – ADB provides no host access and no OS customization capabilities. Customers who are looking for custom requirements and host access will use OCI DbaaS services, where customers can choose from VMs (DbaaS VM images), BM options (DbaaS bare metal services), and Exadata shapes, which include Exadata Cloud Infrastructure (ExaCS) and ExaC@C deployments within the Oracle Cloud Infrastructure portfolio of services.

Let’s discuss having no access to the host OS and no OS customization capabilities a bit. This means a lot when it comes to operational efficiency and standardization. No root or sysdba logins are allowed – the only logins allowed are admin, privileged default ADB user, or regular database user. It means no call-outs to the OS – thus, preventing installation or modification of any software on the system. It is sealed from external administrative access and powered by AI. ADB eliminates any possibility of misconfiguration, database vulnerabilities, malicious activities, and human errors. Database clients can connect securely using a TLS wallet. Oracle manages all the operational aspects to make sure you focus on your application and leave SLAs, patching the OS, database upgrades, security, and several performance-tuning aspects to be part of the autonomous capabilities of the offering.

Some of the stats on database manageability are as follows:

• More than 39% of DBAs handle 50 or more databases (source: From Database Clouds to Big Data: 2013 IOUG Survey on Database Manageability)
• Challenges with the typical patch management process – it’s complex, time-consuming, and involves dependency on multiple stakeholders
• Most companies face high downtime because of a lack of standardization across database fleets within an organization
• Building high availability for databases takes significant time, effort, and expertise, and an enterprise needs it at the click of a button

Quick note

The Independent Oracle Users Group (IOUG): The major focus of the IOUG is on Oracle technology and database advocates. It promotes empowerment through education so that the users can be more productive in their work related to these technologies and also help take better business decisions through providing technology direction and networking opportunities, sharing best practices, and delivering education.

Now, let’s go over some typical considerations that a customer can evaluate when implementing an Autonomous Database. Unlike on-premises deployments, many steps are not needed with Autonomous Databases and because of this, it is easy to deploy as well. Still, there could be several considerations, such as the level of automation and functionality required, workload characteristics of databases such as ATP, ADW, or AJD, provisioning and loading data to Autonomous Databases, connecting your applications to them, and many more.

Oracle ATP supports all operational business systems, including both departmental as well as mission-critical applications, but unlike other cloud providers, ATP doesn’t just support one transaction processing use case; it can also support mixed workloads where you have a mixture of transaction processing, reporting, and batch processing, making it the perfect platform for real-time analytics based on operational databases. This enables users to get immediate answers to any question.

Integrated ML algorithms make it the perfect platform for applications with real-time predictive capabilities. Advanced SQL and PL/SQL support make it the perfect platform for application developers, as developers can instantly create and effortlessly use ATP, eliminating any dependence and delays on others for hardware and software. The fact that it’s self-tuning also eliminates any need for database tuning and accelerates developer productivity. With the availability of APEX within ATP, you can deploy applications faster for their use case or modernize legacy applications with them.

Oracle ADW supports all types of analytical warehouses and decision support database workloads. ADW is particularly well-suited to creating new dependent or independent data marts that allow analytical projects to be started easily. It is a good environment for sandbox experimentation on the part of data scientists, sifting through data and storing large amounts of data and data lakes. It includes analytics and visualization tools, Oracle Machine Learning and Oracle Data Visualization Desktop, and provides an end-to-end environment for application development, data analysis, and fast, flexible database services.