Oracle Autonomous Database is a self-managing database that delivers end-to-end automation of tasks traditionally performed by DBAs. It is available in two infrastructure choices, Shared Exadata Infrastructure and Dedicated Exadata Infrastructure. With Shared, as the name implies, multiple tenants share the same Exadata machine. With Dedicated, customers have their Exadata isolated from other tenants. It offers more control on infrastructure, software, and maintenance lifecycle, including the separation of environments for Production, Development, Test, etc.
A typical use case for Exadata deployment is database consolidation, i.e., the ability to over-provision CPU so that you can assign multiple databases to a physical core. This ability is beneficial for running non-production databases such as Development or Test environments and other non-critical databases where the workload does not justify a whole CPU core. Exadata allows companies to reduce cost without sacrificing the platform’s performance, availability, and security.
This blog describes how you can now achieve similar database consolidation on Autonomous Database Dedicated using partial OCPU instead of a whole OCPU. This feature applies to Autonomous Database on Dedicated Infrastructure and Autonomous Database on Cloud@Customer.
Before Oracle Database Release Update 19.11, the maximum number of Autonomous databases that you could provision was equal to the number of OCPUs on the Exadata Infrastructure, with the smallest database being a single OCPU. Therefore, on an Exadata quarter rack with 100 OCPUs, 100 was the maximum number of Autonomous databases you could create. Another related constraint was the minimum storage size of 1 TB per database.
From Release Update 19.11 onwards, you can now provision Autonomous databases using fractional OCPU and storage in GBs. Fractional OCPU means you can create databases with less than 1 OCPU using fractional units, from 0.1 to 0.9 OCPU, with up to 10 databases running on a single OCPU. Using the previous example, you can provision up to 1000 Autonomous databases on an Exadata quarter rack. Along with fractional OCPUs, you can now provision storage in GB instead of TB, with a minimum storage of 32GB and a scaling increment of 1GB. So, instead of assigning 1TB for a 90GB development database, Autonomous database users can now allocate 100GB for better storage efficiency. Like Autonomous databases with integer OCPU and storage allocation in TB, Autonomous databases with fractional OCPU and storage allocation in GB can be scaled up or scaled down with support for conversion from fractional to integer and GB to TB or vice versa with no downtime.
To create an Autonomous Transaction Processing database with fractional OCPU and storage allocation in GB, enter a decimal OCPU count between 0.1 and 0.9 and specify the storage size in GB on the Create Autonomous Database page. Fractional OCPU is for less than one OCPU only. For OCPU equal to or greater than one, the increment must be in integer.
All Autonomous Database features such as Auto Scaling, Cloning, and Autonomous Data Guard are supported with fractional OCPUs. You can develop and test your production database functionalities such as DR failover with minimal OCPU and storage allocations.
As with integer OCPU Autonomous databases, fractional OCPU databases will get performance-related resources allocated proportionally based on the number of OCPUs chosen. For example, an Autonomous database with 0.3 OCPU will get memory and concurrent sessions allocation that is 30% of the memory and concurrent sessions allocation for a single OCPU Autonomous database.
A critical difference between fractional and integer OCPU is the availability of the predefined database services; these are connection types created at database creation time. Autonomous Data Warehouse with fractional OCPU supports only low service with its TCP and TCPS counterparts (low, low_tls, low_ro, low_ro_tls). Autonomous Transaction Processing with fractional OCPU supports both tp and low services.
Billing for fractional OCPU usage is similar to integer OCPU usage; the total active OCPUs (both integer and fractional) for an Autonomous Container Database are aggregated and then rounded to the nearest integer OCPU. For example, a container database with 38 Autonomous Transaction Processing databases with 0.1 OCPU will be billed as 4 OCPUs.
Fractional OCPU and granular (GB) storage enable Autonomous Database users to reduce costs through database consolidation further. Utilizing the power of the Exadata Infrastructure allows greater consolidation density without sacrificing the platform’s performance, availability, and security. To get started, head to our technical content section here.