Oracle Workspace Manager is a feature of Oracle Database that provides the infrastructure for developers to create workspaces to maintain multiple versions of a set of tables. Developers can work on a copy of the data within a workspace that is visible only to them and not visible to other users of the database accessing production data. Changes they make to the data are isolated to the workspace. When a developer has finished working on data in a workspace, they can merge it with production data.
Oracle Workspace Manager is now available on Oracle Autonomous Database Serverless.
With Oracle Workspace Manager, developers can
◉ Manage a collection of updates and inserts to tables as a unit before adding them to production data
◉ Support a collaborative development effort with multiple workspaces and workspace hierarchies to concurrently work on subprojects
◉ Explore “what-if” scenarios
◉ Keep a history of changes to the data
◉ Manage “long-transaction” scenarios that are complex -long-duration database transactions can take days to complete - while users are accessing the same database in a production application
The diagram to the right illustrates how a company can use workspaces to explore proposed changes in an example geospatial application. The LIVE workspace is maintained as the single source of truth. The Parcel A Subdivision workspace and the Parcel B Zoning workspace are used to contain the updates from those components of the application. When those projects successful the company can merge the updates into the LIVE workspace. Similarly, within the Parcel A Subdivision workspace, we have two sub-workspaces – open space and conventional. If approved, those projects can be merged into the Subdivision workspace.
The benefits of utilizing Oracle Workspace Manager include retaining a history of changes indefinitely and saving time, money, and resources by eliminating the need to maintain multiple database versions. Oracle Workspace Manager allows for differencing and conflict detection/resolution, partial and complete merge/refresh of workspaces or tables, and garbage collection operations to optimize version storage.
The Oracle Cloud Infrastructure (OCI) Big Data service with Apache Hadoop is a fully managed cloud service from OCI that allows you to process big data workloads using popular open source frameworks, such as Hadoop, Spark, Hive, and HBase. One of the features of OCI Big Data is the ability to create and manage Hadoop clusters of different profiles or types. In this blog post, we discuss the cluster profile feature in OCI Big Data, its benefits, and how to use it.
What is OCI Big Data?
OCI Big Data is a cloud-based big data processing service offered by OCI. The fully managed platform enables customers to process large amounts of data using popular open source big data frameworks, such as Hadoop, Spark, Hive, and Kafka. The service is designed to simplify the process of deploying and managing big data solutions, and you can integrate it with other OCI services and on-premises systems.
Use cases for Oracle Big Data
The following examples show the top use cases for OCI Big Data:
ETL processing: Extract, transform, load (ETL) is a common use case for OCI Big Data. You can use OCI Big Data to process large amounts of data, transform it into a format suitable for analysis, and load it into a data warehouse or other storage system.
Data analysis: You can use OCI Big Data for data analysis and data exploration. You can use OCI Big Data to run Apache Spark jobs to analyze data and generate insights—useful for business intelligence, data visualization, and machine learning (ML) applications.
Machine learning: You can use OCI Big Data for ML applications to train models on large datasets and then use the models for prediction and other tasks.
Log processing: With OCI Big Data, you can process analyze log data from web servers, application servers, and other sources to identify patterns and trends.
Batch processing: You can use OCI Big Data to process large amounts of data in batches, for example, to generate reports or perform calculations.
Real-time processing: You can use OCI Big Data to process streams of data in real-time, for example, to perform fraud detection or anomaly detection.
Why customers love OCI Big Data service
Customers love OCI Big Data, a cloud-based big data analytics service, for the following common reasons:
Scalability: OCI Big Data can easily scale to handle large amounts of data and processing power, enabling customers to gain insights quickly and efficiently.
Compatibility: OCI Big Data supports various open source big data frameworks, such as Hadoop, Spark, Hive, and Kafka, which allows customers to use the tools they’re familiar with and use existing code.
Security: OCI Big Data offers robust security features, including encryption at rest and in transit, and integrated authentication with OCI Identity and Access Management (IAM) service, providing customers with peace of mind that their data is protected.
Flexibility: Customers can choose to deploy OCI Big Data in various ways, including using preconfigured clusters or creating custom clusters with specific configurations, enabling them to tailor the service to their specific needs.
Integration with other OCI services: OCI Big Data integrates with other OCI services, such as OCI Data Catalog, OCI Data Flow, and OCI Lake House, and OCI makes it easy for customers to build end-to-end solutions for their big data needs.
What is a cluster profile?
A cluster profile in OCI Big Data represents a preconfigured set of resources optimized for a particular workload or use case. Each cluster profile has a predefined set of configuration parameters that are optimized for a specific data processing job. For example, OCI offers cluster profiles for Hadoop, Spark, HBase, Hive, and Trino (Interactive query), each designed for specific workloads and use cases.
Hadoop
The Hadoop cluster type in OCI Big Data is designed to work with Hadoop Distributed File System (HDFS) and MapReduce. It’s ideal for batch processing, such as data warehousing, log analysis, and ETL. The Hadoop cluster type comes with Hadoop, Hive, Pig, and Oozie preinstalled, making it easy to get started with big data processing.
Spark
The Spark cluster type in OCI Big Data is designed to work with Apache Spark, an open source data processing framework that supports both batch and streaming data processing. It’s ideal for real-time data processing, machine learning, and graph processing. The Spark cluster type comes with Spark, Hive, and Jupyter preinstalled, making it easy to start using Spark for big data processing.
HBase
The HBase cluster profile in OCI Big Data is designed to work with Apache HBase, an open source NoSQL database that runs on top of Hadoop. It’s ideal for storing and retrieving large amounts of structured data, such as sensor data, social media data, and financial data.
Trino
This cluster profile is for interactive querying of large datasets. Trino returns results to you as soon as they’re available. This availability offers data analysts and data scientists the ability to query large amounts of data, test hypotheses, run A/B testing, and build visualizations or dashboards.
Kafka
This cluster profile is designed for streaming data processing and supports Apache Kafka.
Hadoop Etxended
We used this cluster profile before the profile feature was introduced.
Benefits of cluster profiles
The use of cluster profile provides the following benefits:
Faster cluster deployment: The use of preconfigured cluster profiles speeds up the deployment process by reducing the amount of manual configuration required.
Better performance: Cluster profiles are optimized for specific workloads, providing better performance compared to a generic cluster setup.
Simplified management: Each cluster profiles comes with preconfigured services, reducing the need for manual configuration and simplifying cluster management.
How to use cluster profiles in OCI Big Data
To create an OCI Big Data cluster using a specific cluster profile, use the following steps:
In the Oracle Cloud Console, navigate to the OCI Big Data service.
Click the Create cluster button.
Enter the cluster name and admin password.
Select the checkbox for Secure and Highly Available (HA) to make the cluster secure and highly available.
Select the distribution and version of Hadoop from either Oracle’s Distribution of Hadoop (ODH) or Cloudera’s Distribution of Hadoop (CDH).
Select the cluster profile that best suits your use case from the menu. You can also select the version of the cluster type that you want to use.
Select from the Compute shape, block storage for master and utility, and the number of Compute shape options for the worker nodes.
Provide the network related details, such as CIDR Block, virtual cloud network (VCN), and subnet details.
Select your encryption type: Oracle-managed or customer-managed.
Click Create to provision the Big Data cluster.
When the cluster is created, off you go! You can use it to process Big Data workloads using the services and tools enabled by default.
An Oracle Database Administrator (DBA) is a professional responsible for managing, maintaining, and securing an organization's databases. They work closely with software developers, system administrators, and other IT staff to ensure that databases function correctly and data is accurate, accessible, and secure. DBAs are responsible for designing, implementing, and maintaining the organization's database infrastructure, including the hardware, software, and security systems.
In addition to designing and maintaining databases, DBAs are responsible for ensuring the data is backed up and recoverable in case of a disaster or outage. They monitor the performance of the database systems and make adjustments to improve performance and efficiency.
They are also responsible for managing user access to the databases, ensuring that users have the appropriate permissions and access levels to perform their job duties while maintaining the security and integrity of the data. DBAs must have strong technical skills in database design, management, and security and excellent communication and problem-solving skills to work effectively with other IT staff and stakeholders.
Systems DBA: Concentrates on the technical aspects of managing the database infrastructure, including installation, configuration, and maintenance of the hardware, software, and network systems.
Application DBA: Focuses on managing and maintaining specific database applications. They work with developers and system administrators to ensure that the application runs efficiently and effectively and that the data is accurate and accessible.
Database Security Administrator: Concentrates on managing and maintaining the database system's security. They work to contain unauthorized access to the data and ensure that sensitive data is protected from internal and external threats.
Data Architect: Focuses on designing and developing the data structures and schema for the database system. They work with developers, business analysts, and other stakeholders to ensure the database is optimized for the organization's requirements and requirements.
Data Warehouse Administrator: Manages and maintains complex business intelligence and analytics databases. They ensure that data is accurate, accessible, and available for analysis.
Cloud Oracle Database Administrator: Focuses on managing and maintaining databases hosted in the cloud. They work with cloud service providers and other IT staff to ensure the database system is optimized for performance and efficiency in the cloud environment.
Day-to-Day Activities of an Oracle Database Administrator
The day-to-day activities of an Oracle Database Administrator can vary depending on the organization and the specific responsibilities of the role. However, here are some everyday tasks that a DBA might perform daily:
Monitor Database Performance: DBAs must monitor the performance of the database system, including CPU usage, memory usage, and I/O throughput. They use monitoring tools to determine bottlenecks and performance issues and make adjustments to optimize performance.
Backup and Recovery: DBAs must ensure that the database is backed up regularly and that backups are recoverable in case of a disaster or outage. They may also perform regular testing to ensure that backups are working correctly.
Security: DBAs must manage and maintain the security of the database system. They work to control unauthorized access to the data and ensure that sensitive data is protected from internal and external threats. This may include configuring security settings, managing user access, and monitoring for security breaches.
Maintenance: DBAs perform regular maintenance tasks to ensure the database system functions appropriately. This may include applying patches and updates, optimizing database performance, and performing routine maintenance tasks such as defragmentation.
Troubleshooting: DBAs must be able to recognize and troubleshoot issues that arise in the database system. They use diagnostic tools to identify the root cause of problems and work to resolve them quickly and efficiently.
Capacity Planning: DBAs must plan for the database system's future growth and capacity needs. They may analyze usage patterns and trends to decide when additional resources will be needed and make recommendations for upgrades or changes to the system.
What Is the Workplace of an Oracle Database Administrator Like?
The workplace of an Oracle Database Administrator can vary depending on the organization they work for. A DBA typically works in an office, although remote work is becoming increasingly common.
DBAs work with computer systems and software, meaning they spend most of their time in front of a computer. They may work alone or as part of a team, depending on the size of the organization they work for. They may also work closely with other IT professionals, such as developers and network administrators, to ensure the organization's technology systems function correctly.
DBAs may work standard office hours but may also be required to work outside regular business hours to complete maintenance or upgrades on the organization's databases. This can include working weekends or evenings when the system is least busy to minimize the impact of downtime.
Regarding the physical environment, DBAs typically work in a quiet, temperature-controlled office with good lighting and ergonomic workstations. They may also require access to specialized equipment, such as servers and storage devices, to perform their job duties.
Oracle Database Administrator Salary
The average salary for an Oracle Database Administrator in the US is $131,342. The average additional cash payment for a Database Administrator in the US is $9,250. The average total wage for a Database Administrator in the US is $140,592. Database Administrator salaries are based on responses gathered by Built In from anonymous Database Administrator employees in the US.
Conclusion
The Oracle Database Administrator role is here to stay regarding data administration, but the name might require some tweaking. The digital age has resulted in massive growth in unstructured data, such as text, images, sensor information, audio, and videos, on account of e-commerce, IoT, AI, and social media. As a result, the job title ‘database administrator’ seems to give way to ‘Oracle Database Administrator’ to cater to the management of both structured (database) and unstructured (big data) data sets.
Oracle Real Application Security (RAS) is the industry's most advanced technology, supporting application security requirements. RAS is the next-generation fine-grained access control mechanism for the Oracle Database – similar to Oracle Virtual Private Database(VPD) but more flexible and easier to maintain. It provides an application access control framework within the database enabling n-tier applications to define, provision, and enforce their security requirements declaratively. Oracle RAS introduces a policy-based authorization model that recognizes application-level users, privileges, and roles within the database and then controls access to static and dynamic collections of records representing business objects. Like VPD, RAS lets you create a security policy once, and enforce that policy regardless of how the data is accessed – via the application, via SQL*Plus, or through other interactive mechanisms.
The out-of-the-box integration of Oracle RAS with Oracle APEX eliminates custom development for securing application data, thus providing end-to-end application security.
Security enforcement in multi-tier applications using Oracle RAS:
Use case:
Let’s suppose you want to restrict the application users “blake” & “king” to access only the rows belonging to the department ID 10 & 20, respectively, in the “emp” table under the “hr” schema. For this example, we'll use APEX as our developement framework.
High-level steps to achieve the use-case:
Create a DB role and grant privileges on the table that you want to protect to the DB role.
Create a RAS admin user and assign privileges to the RAS admin user.
Create an application role and grant the DB role to the application role.
Create application users and grant application roles to the application user.
Enable RAS on the instance level in APEX by logging in as an admin user.
Enable RAS on each application by logging into the APEX workspace.
Create Security Class as required.
Create ACLs and associate application roles to the ACLs
Create Data Security Policy.
Apply data security policy to the table.
Access the table as an application user through APEX.
Below are the names used in this example:
Database schema : HR
DB Table : EMP
RAS admin user : RASADM
Database Role : DB_EMP
Application Roles : DEPT10 & DEPT20
Application Users : BLAKE & KING
1. Create a DB role by logging in to the autonomous database as a database ADMIN user and grant privileges on the table that you want to protect to the DB role.
Create the database role DB_EMP and grant this role the necessary table privileges.
create role db_emp;
grant insert,update,delete,select on hr.emp to db_emp;
2. Create a RAS admin user, “RASADM” and assign privileges to the RAS admin user.
create user rasadm;
password rasadm; --enter the password for RASADM
grant CREATE SESSION to rasadm;
Grant DB role created in step 1 to the RAS admin user.
grant db_emp to rasadm with admin option;
Real Application Security works the same on Autonomous Database as on an on-premises Oracle Database except you need to perform the following ADMIN tasks before using Real Application Security on Autonomous Database:
To create Real Application Security users/roles, you need the PROVISION system privilege.
As the ADMIN user run the following command to grant this privilege to a database user:
5. Enable RAS on the instance level first in APEX by logging in as an admin user.
Login to APEX as ADMIN user.
Click on Manage Instance.
Click on Security.
Click on Real Application Security and ensure the option "Allow Real Application Security" is set to Yes. By default, this option is set to yes on the autonomous database.
6. Enable RAS on application by logging into APEX workspace. In this example I am logging into HR workspace in APEX.
Click on App Builder
Click on the application that you want to enable RAS.
Click on Shared Components.
Click on Authentication Schemes.
Select the default scheme – Oracle APEX accounts..
Click on Real Application Security.
Enable the RAS Mode by selecting Internal Users or External Users based on the requirement. In this example, I am opting for Internal Users and click on Apply Changes.
7. Create Security Class as required.
If there’s any requirement to mask any column or row data to a specific user, then you can use a security class to achieve the same. I am skipping security class creation as it’s out of scope for this use case.
8. Create ACLs and associate application roles(dept10 & dept20) with the ACLs.
Create ACLs:
declare
aces xs$ace_list := xs$ace_list();
begin
aces.extend(1);
-- DEPT10_ACL: This ACL grants dept10(application role) the privilege to view and update all
11. Now, access the table as an application user through APEX. I followed the below steps to achieve the same.
Log into the workspace.
Click on ‘Administration’ and select ‘Manage Users and Groups’.
Click on create user. Create the same application users created in Step 4.
Provide the mandatory details: Username, Email Address & Password and click on Create User. Repeat this step to create all the application users. In this example I am creating the users "blake" & "king".
Now, create the application roles in APEX. Create the same application roles created in step 3.
For this click on app-builder, then select the application, and click on shared components.
Click on Application Access Control.
Click on Add Role.
Provide the role name and description(optional) and click on Create Role. Repeat this step to create all the application roles.
In this example, I am creating the application roles "dept10" & "dept20".
In the same window, scroll down and click on “Add User Role Assignment”. This associates the application role created above with the application user.
Provide the application User Name, check the Application Role you want to assign the user to and then click on Create Assignment.
You’ll be able to see the role and assignments as shown below.
Now run the application by providing the application username and password.
In this example I am logging in as "blake" user.
Click on the table.
You’ll see only the rows that the user is allowed to see.
In this example, the application user “blake” could see only the rows belonging to the department number 10.
Oracle is excited to announce the next generation of Exadata Database Machine platform, the Oracle Exadata X10M. Built on more than a decade of high-performance database hardware and software innovations, Exadata X10M brings extreme scale and better price performance to the ideal platform for running Oracle Database.
Overview
Exadata X10M delivers unrivaled performance, availability, and scalability for all database workloads. Starting at the same price as the previous generation, Exadata X10M also provides significantly more capacity and dramatically greater value than previous generations. Today, thousands of large and small enterprises run their most critical and demanding workloads on Exadata, including the majority of the largest financial, telecom, and retail businesses.
The latest Exadata generation features fourth-generation AMD EPYC™ processors and delivers dramatic performance improvements with up to 3x higher transaction throughput and up to 3.6x faster analytic queries on database servers. With X10M, High Capacity storage servers can now hold 22% more data, while all-flash Extreme Flash Storage Servers now offer 2.4x the capacity of the previous systems. Database servers support 50% higher memory capacity enabling more databases and larger memory-intensive workloads to run on the same system. The combination of improved performance and more storage and memory capacity enables greater levels of database consolidation and dramatically lower costs for all database workloads, with the price of Exadata X10M High Capacity systems remaining the same as the previous generation. The greater compute and storage density offered by Exadata X10M platforms also reduces the size of the systems customers require to meet their needs, lowering data center costs for power, cooling, and floor space, and improving data center sustainability.
Exadata X10M
Exadata X10M is built using the latest processors, networking, and storage technologies and includes numerous optimizations to the system hardware, Exadata system software, and Oracle Database software to deliver unparalleled performance and value for online transaction processing (OLTP), analytics, machine learning (ML), and mixed workloads. Exadata’s scale-out architecture, combined with the impressive scale-up capabilities provided by fourth-generation AMD EPYC™ processors that power Exadata X10M, enables organizations to meet their sophisticated data management needs in public cloud, hybrid cloud, or on-premises deployments.
Exadata X10M platforms for deployment in an organization’s data centers include the Exadata Database Machine X10M and the Exadata Cloud@Customer X10M. Exadata Cloud@Customer uses the same architecture, software, and infrastructure as the Exadata Database Machine to enable customers to run Oracle Cloud Infrastructure’s (OCI) automated Oracle Exadata Database Service and fully managed Oracle Autonomous Database in their data centers so they can benefit from OCI automation and economics. Exadata Database Service and Autonomous Database also run on AMD EPYC™ processor based Exadata Cloud Infrastructure in OCI. Packed with tremendous OLTP and analytics performance and a substantial increase in consolidation capabilities, an Exadata X10M quarter rack still has the same price as an Exadata X9M - an amazing value for an incredible system. The enhancements found in Exadata X10M dramatically reduce infrastructure spending, lower system and database administration, and cut energy consumption compared to Exadata X9M platforms.
High-performance OLTP and modern workloads such as IoT, blockchain, gaming, financial trading, and eCommerce require the world’s fastest OLTP Database machine, which just got even faster. Exadata X10M database servers each have an awesome 3X the number of cores of the Exadata X9M database servers and a near meteoric 1 TB/sec of memory bandwidth. With each database server core in Exadata X10M running OLTP workloads faster than their equivalents in the prior generation, customers can achieve up to 3X the total OLTP throughput.
Exadata X10M storage servers each boast 2.8 million 8k read I/Os per second, an impressive 21% increase over X9M! Utilizing DDR5 DRAM in intelligent storage servers, Exadata RDMA Memory (XRMEM) read latency drops from 19 microseconds to an astonishing 17 microseconds with Exadata X10M. As with all Exadata performance metrics, these are real-world, end-to-end database workload numbers, not low-level I/O metrics using small-sized test workloads typically used by storage vendors.
Analytics workloads enjoy a healthy performance boost as well. Exadata X10M increases the number of processing cores in each storage server to 64, enabling greater parallelism for analytics queries. Smart Scan throughput offloads SQL processing to the Exadata intelligent storage servers, topping the 1 TB (Terabyte) per second mark in a single rack.
Database consolidation on Exadata reduces the complexity and overhead of running more and larger databases. The immense increase in the number of cores and memory in Exadata database servers, flash and hard drive capacity, and SQL processing cores in Exadata storage servers means you can run more Oracle databases on less Exadata infrastructure than ever. Higher consolidation densities reduce CAPEX and administration and improve energy efficiency so you can run your Oracle Database fleet more efficiently.
The remainder of this blog details many astounding advances with Exadata X10M. We also recommend you read the Exadata Cloud@Customer X10M blog and the family of Oracle Exadata web pages for more information.
Exadata Hardware
Exadata X10M Database Server
Exadata X10M database servers use two 96-core 4th-generation AMD CPUs, delivering a stunning 3X increase in cores and greater per-core performance than the Exadata X9M generation. Memory size in Exadata X10M has increased to meet customer demands for increased database consolidation and to support increased CPU core density.
Memory configurations of 512 GB, 1.5 TB, 2.25 TB, and 3 TB DDR5 DRAM per database server are now available. Memory bandwidth in Exadata X10M database servers is 2.5X that of Exadata X9M, greatly accelerating memory bandwidth-sensitive operations.
Local storage on the database servers continues to utilize two 3.84 TB NVMe SSD drives, expandable to four 3.84 TB drives, which are all hot-swappable.
Exadata X10M replaces the PCIe 4 data interface for the network cards with PCIe 5 and adopts the latest generation of dual-port RDMA over Converged Ethernet (RoCE) network cards to increase throughput to the private network. In addition, X10M supports up to five client network interface cards for more flexible network connectivity.
Exadata X10M High Capacity Storage Server
Each Exadata X10M High Capacity Storage Server uses two 32-core 4th-generation AMD CPUs, doubling the number of storage server cores in Exadata Database Machine and increasing the core count from 24 to 32 for Exadata Cloud@Customer X10M when compared to X9M. Memory gets a massive upgrade in the storage tier to 1.5 TB DD5 DRAM, up from 256 GB in the X9M, to accommodate Exadata RDMA Memory (XRMEM).
Like the Exadata Database Server, memory bandwidth in storage servers increases by up to 2.5X. Each storage server includes four performance-optimized Flash cards, each increasing in size to 6.8 TB from the previous generation’s 6.4 TB. The RoCE Network Fabric moves to the same dual-port RoCE network cards used in the database server. The 12 hard disk drives increase in capacity from 18 TB to 22 TB each, bringing the total raw capacity per storage server from 216 TB to 264 TB, up a healthy 22% from X9M.
Exadata X10M Extreme Flash Storage Server
All new with Exadata X10M, the Extreme Flash Storage Servers add a new storage tier with four capacity-optimized 30.72 TB flash drives for an aggregate, raw storage capacity of 122.88 TB, an impressive increase of 2.4X over X9M’s 51.2 TB.
As with the X10M High Capacity Storage Server, four 6.8 TB performance-optimized Flash cards are dedicated to the Flash Cache. Extreme Flash Storage Servers align with the High Capacity Storage Server, using the latest 32-core 4th-generation AMD CPUs, memory upgrades, and dual-port RoCE network cards.
Exadata X10M Extended Storage Server
The Exadata X10M Extended Storage Servers use the latest 32-core 4th-generation AMD CPU. Memory increases from 96 GB to 128 GB. Like the Database and other Storage Servers, the RoCE Network Fabric utilizes dual-port RoCE network cards. The 12 hard disk drives increase in capacity to 22 TB each, with a total capacity of 264 TB per storage server, up from 18 TB each and 216 TB per storage server in X9M, a 22% increase.
Exadata X10M Storage Expansion Rack
Exadata Storage Expansion Rack X10M starting configurations support the latest Exadata X10M High Capacity and Extreme Flash Storage Servers. Additional High Capacity, Extreme Flash, and Extended Storage Servers can be added to existing X8M, X9M, and X10M Storage Expansion Racks, ensuring customers can scale their storage needs to meet the most demanding database deployments. The Exadata X10M Extended Storage Servers use the latest 32-core 4th-generation AMD CPU. Memory increases from 96 GB to 128 GB. Like the Database and other Storage Servers, the RoCE Network Fabric utilizes dual-port RoCE network cards. The 12 hard disk drives increase in capacity to 22 TB each, with a total capacity of 264 TB per storage server, up from 18 TB each and 216 TB per storage server in X9M, a 22% increase.
Scalable Licensing
Capacity On Demand (CoD) has been available since Exadata X4 and continues on Exadata X10M to enable customers to reduce the required database software licenses. At installation time, a minimum of 14 cores must be enabled on each X10M database server. Oracle Exadata Deployment Assistant (OEDA) implements CoD during the installation process. You can then increase the active core count over time as the demand for compute resources on the database servers increases.
Exadata System Software 23.1
Oracle announced Exadata System Software 23.1 in March 2023. In addition to supporting X10M hardware, 23.1 adds several features to Exadata, including an operating system upgrade from Oracle Linux 7 and UEK 5 to Oracle Linux 8 and UEK 6. Exadata System Software continues to take the Exadata Database Machine to new levels with the following additional new features:
Oracle Linux 8 and UEK6
The core of the 23.1 release is the upgrade to Oracle Linux 8.7 and UEK6, which ensures platform maturity and strong ecosystem compatibility.
New compression algorithm for Database In-Memory Columnar Caching
Beginning with X10M, customers using Database In-Memory Columnar Caching in Storage Servers gain up to a 25% increase in the effective capacity by virtue of a new compression algorithm. This optimization increases the capacity and efficacy of In-Memory Columnar formatted data in the storage servers.
KVM Update with X10M
With the increase in max memory on the X10M Database servers comes an increase in memory available to virtual machines. The maximum amount of memory that can be allocated to virtual machines is 2.73 TB per database server on a 3 TB database server configuration. So, a single virtual machine or multiple virtual machines can utilize a combined footprint of up to 2.73 TB per database server. Remember, you cannot over-provision physical memory; the minimum is still 16 GB for each virtual machine. Exadata X10M continues to allow up to 2X virtual CPU (vCPU) over-provisioning on configurations with more than 512 GB memory and where Capacity-On-Demand is inactive. With two 96-core CPUs (two vCPUs per core) in Exadata X10M, you get a mind-blowing 760 vCPUs (four vCPUs reserved for the host) available per database server.
Centralized Identification and Authentication of OS Users
The database and storage servers have added support for LDAP Identification and Kerberos Authentication. This improves the overall security posture of Exadata and, as the name suggests, centralizes identification and authentication functions of administrator accounts, standardizes password complexity, aging, and reset procedures, and improves the on and off-boarding experience.
Introduction of Exadata RDMA Memory (XRMEM)
Exadata RDMA Memory (XRMEM) in the Exadata X10M storage servers is leveraged as a shared read accelerator. The XRMEM Data Accelerator is a memory cache tier in front of Flash Cache, enabling orders of magnitude lower latency accessing remotely stored data. By utilizing RDMA to access memory remotely, XRMEM Data Accelerator bypasses the network and I/O stack, eliminating expensive CPU interrupts and context switches and reducing latency by more than 10X, from 200 microseconds to less than 17 microseconds. Smart Exadata System Software also ensures data is mirrored across storage servers for fault tolerance. Exadata’s unique end-to-end integration between Oracle Database and Exadata storage servers automatically caches the hottest data blocks efficiently between the buffer cache in database servers and XRMEM and Flash Cache in storage servers. XRMEM is a shared storage tier across all of the storage nodes, which means the aggregate performance of this cache can be dynamically used by any database instance on any database server. XRMEM is a significant advantage over general-purpose storage architectures, which preclude sharing memory and storage resources across database instances.
Supports Grid Infrastructure 19c and newer
Exadata System Software supports Oracle Grid Infrastructure 19.15 and newer and Oracle Database version 11g through 19c. My Oracle Support note 888828.1 details all the software version requirements.
Support for Exadata X10M Hardware
Exadata System Software 23.1, including Oracle Linux 8 and UEK 6, is the foundation for the Exadata X10M family and is fundamental to the extreme scalability of this generation of Exadata systems.
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