E1: DB: JD Edwards EnterpriseOne Support for Oracle Autonomous Database (Doc ID 2687249.1)

Last updated on FEBRUARY 08, 2024

Applies to:

JD Edwards EnterpriseOne Tools - Version 9.2 and later
Information in this document applies to any platform.

Details

JD Edwards EnterpriseOne Support for Oracle Autonomous Database

Oracle JD Edwards supports Oracle Autonomous Database on both Dedicated Exadata Infrastructure and Shared Exadata Infrastructure on Oracle Cloud Infrastructure. Oracle Autonomous Database Dedicated is also available on Exadata Cloud@Customer for customers who want to deploy Autonomous Database in their data center. With this support, customers can integrate their JD Edwards installation on Oracle Cloud Infrastructure with Oracle Autonomous Database on Dedicated Exadata Infrastructure through manual data migration and configuration.

Oracle JD Edwards EnterpriseOne with Oracle Autonomous Database:

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Oracle JD Edwards supports Oracle Autonomous Database on Shared Exadata Infrastructure starting from tools release 9.2.6.

Oracle JD Edwards supports the Oracle Autonomous Database on Dedicated Exadata Infrastructure for the below release levels:

JD Edwards Applications Release 9.2 and above
JD Edwards Tools Release 9.2.4.3 and above
Oracle Autonomous Database 19c (19.7 DBRU and above)

Customers looking for more information regarding the support for Oracle Autonomous Database are encouraged to refer to these documents:

Frequently Asked Questions for Oracle Autonomous Database with Oracle JD Edwards EnterpriseOne:

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Manual deployment of Oracle JD Edwards with Oracle Autonomous Database: With this support, customers can integrate their existing Oracle JD Edwards deployed on Oracle Cloud Infrastructure to Oracle Autonomous Database by manually migrating their data into Oracle Autonomous Database and performing manual configuration.
Note: Currently we do not have any documentation for direct implementation with ADB-D. Only migration scenario has been covered.

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Oracle JD Edwards customers can adopt Oracle Autonomous Database using the manual deployment method described in the above document and benefit from better efficiency and higher level of innovation. Using JD Edwards with Oracle Autonomous Database ensures that customers have a high-performing and highly available system with lower operational costs. By following the best practices described in this document, customers can ensure that they have the right setup, configurations, and topology to get the maximum benefit from Oracle Autonomous Database. By adopting Oracle Autonomous Database with JD Edwards, customers can reimagine IT management and focus more on value-driven innovation.

Also, Oracle JD Edwards recommends that you have the same number of OCPUs and the same storage capacity for Oracle Autonomous Database, as you have for your current database setup in Oracle Cloud Infrastructure. Oracle Autonomous Database is by default deployed as a Real Application Cluster (RAC).

Planned database maintenance with zero downtime: Oracle Autonomous Database enables planned database maintenance with zero downtime for Oracle JD Edwards through extended application continuity service drain time for database connections. This capability enables automatic patching of the database with the latest patches and fixes without any application downtime, manual intervention, and impact on business.

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For any queries on this support, please enter a Service Request (SR) in My Oracle Support (support.oracle.com) regarding the Oracle JD Edwards product for use with the Oracle Autonomous Database.

Support for Automatic and Manual Scaling for Autonomous Database

Starting with Tools Release 9.2.8 (Release 24), Customers using Oracle Autonomous Database can now leverage the automatic scaling and manual scaling capability of Autonomous Database to cater to workloads requiring additional CPU and IO resources. With compute auto scaling, the database can be scaled up to three times more CPU and IO resources from the initial configuration without any manual intervention. With manual scaling, the customer can manually monitor the user load and change the resources accordingly. This ensures optimal performance with better utilization of resources and better preparedness for handling varying business cycles and workloads.