Explore the cutting-edge Oracle Autonomous Database, a revolutionary solution offering a fully automated and adaptive service for diverse workloads. Tailored editions cater to analytics, data warehousing, and transactional needs, while deployment options provide flexibility and customization. Dive into the future of database management with Oracle’s innovative approach.
Introduction
Oracle Autonomous Database stands as a fully automated solution designed to facilitate the development and deployment of application workloads for organizations of all sizes and complexities. This service, featuring a converged engine, supports a wide array of data types, streamlining the entire application development lifecycle—from modeling and coding to ETL, database optimization, and data analysis. Leveraging machine learning for automated tuning, scaling, and patching, Autonomous Database ensures optimal performance, availability, and security across various workloads, including OLTP, analytics, batch, and Internet of Things (IoT). This cutting-edge solution, based on Oracle Database and Oracle Exadata, is accessible on Oracle Cloud Infrastructure (OCI) for both serverless and dedicated deployments, as well as on-premises through Oracle Exadata Cloud@Customer and OCI Dedicated Region.
Oracle Autonomous Database seamlessly blends the adaptability of cloud technology with the efficiency of machine learning, introducing data management as a service. Rooted in over three decades of technical advancements crafted by Oracle to meet the demands of numerous enterprise clients globally, the foundation for Autonomous Database encompasses key components:
- Oracle Database Enterprise Edition
- Exadata Database Machine
- Oracle Cloud Infrastructure
- Oracle’s Best Practices
- Oracle’s Knowledge Base
- Machine Learning
This innovative blend of technologies empowers Autonomous Database to operate as a self-driving, self-securing, and self-repairing database. This autonomy enables customers to channel their efforts towards developing and delivering solutions that directly enhance their business value. While each technology provides robust capabilities independently, their convergence within the Oracle Autonomous Database marks a revolutionary milestone.
Why Enterprise Edition?
The underpinning of Autonomous Database originates from Oracle Database Enterprise Edition, a longstanding database trusted by customers for running diverse workloads like Data Warehouse, Analytics, and Transaction Processing. Autonomous Database streamlines operations through automated configuration settings, eliminating management intricacies as further explained in this document.
This autonomous database is constructed upon and automates several advanced database technologies exclusive to Oracle, including:
- Real Application Clusters for scale-out, failover, and online patching
- Online operations for seamless schema changes
- Active Data Guard for database-aware Disaster Recovery
- Parallel SQL for optimal throughput
- Database Containers for enhanced agility
- Database In-Memory for superior performance
- Transparent Database Encryption for robust data protection
- Database Vault for role segregation
The Autonomous Database Service
The inherent capabilities of the Oracle Database, functioning as a converged database, facilitate the provision of the Autonomous Database in two editions precisely customized to specific workloads adhering to Oracle’s Best Practice recommendations. Oracle Autonomous Data Warehouse (ADW) is optimized for tasks such as Data Warehousing, Data Marts, Data Lakes, and Machine Learning workloads. On the other hand, Oracle Autonomous Transaction Processing (ATP) is fine-tuned for On-Line Transaction Processing, Batch, reporting, IoT, application development, machine learning, and mixed workload environments.
Autonomous Data Warehouse (ADW)
True to its name, Oracle Autonomous Data Warehouse (ADW) is designed to cater to Data Warehouse and associated workloads, including Data Marts, Machine Learning, or as part of a Data Lake deployment. These systems and databases are usually segregated from Transaction Processing applications and are crafted to fulfill distinct business requirements. Data Warehouses commonly adopt data modeling methodologies like Star Schema and other techniques to ensure that data structures align with the needs of business users engaged in data analysis and Data Scientists conducting trend-analysis. With large volumes of data processed in bulk or streamed into the database, Data Warehouses often rely on summary data representation and highly parallel SQL to ensure swift response times. Oracle Autonomous Data Warehouse is precisely crafted to cater to these specific use cases.
Autonomous Transaction Processing (ATP)
Oracle Autonomous Transaction Processing (ATP) extends the same autonomous capabilities found in ADW to the realm of Transaction Processing and mixed workloads. ATP is specifically designed for intricate Transaction Processing workloads that encompass operational reporting and/or batch data processing. The capacity to execute mixed workloads within a single database obviates the need to transfer data from a Transaction Processing database to a separate reporting or analytics system. This capability not only simplifies application complexity but also eradicates the wait-time associated with data movement between Transaction Processing and Analytic database services. ATP supports IoT and machine learning alongside OLTP. By automating the creation and management of databases, ATP significantly streamlines the process of application development.
Serverless and Dedicated Exadata Infrastructure.
The Autonomous Database can be implemented on either Serverless or Dedicated Exadata Infrastructure, with Oracle assuming complete responsibility for all facets of service operation in both scenarios. Autonomous Database Serverless offers the smallest minimum commitment, while Dedicated Exadata Infrastructure affords customers greater control over infrastructure operations. Each of these options delivers significant benefits, as detailed below.
What is the difference?
Oracle Autonomous Database Serverless provides customers with the advantages of complete isolation of data and system resources while sharing infrastructure with other customers. This deployment option requires a minimum commitment of just one hour, one OCPU, and one Terabyte of database storage. It can be instantly scaled in terms of CPU and/or storage fully online, allowing users to pay only for the resources utilized. This option is well-suited for line-of-business and departmental applications, data marts, and serves as an excellent sandbox for Data Scientists or developers.
In the Serverless deployment, all customers and their databases operate within a unified and standardized set of operational processes. They run the same software versions, update levels, and security patches, all of which are scheduled and uniformly applied by Oracle’s autonomous service software. Serverless is an excellent choice for customers who want to be database users without concerns about database operations, including software updates.
On the other hand, lets understand what a dedicated system has to offer.
With Dedicated Infrastructure, customers have their dedicated Exadata infrastructure in the Oracle Cloud, essentially providing them with a Private Database Cloud within the Oracle Public Cloud. Oracle Autonomous Database on Dedicated Infrastructure operates within a hardware-enforced virtual cloud network, ensuring the highest level of isolation from other tenants. Users can easily configure one or more Container Databases on their dedicated infrastructure, each of which can contain one or more Pluggable Databases.
Dedicated Infrastructure offers customers the opportunity to customize Operational Policies governing the provisioning of new databases, the timing of updates, availability, and database density on the infrastructure. Having control over database versions and the timing of upgrades is particularly crucial for applications sensitive to version and release differences. Despite the customization of these Operational Policies, all operations remain fully automated by Oracle.
With Dedicated Infrastructure, customers can define “fleet administrators” who manage the overall service, as well as individuals who can deploy and manage databases themselves. It serves as an ideal platform for customers seeking to reassess their IT strategy and transition some or all of their database estate to a Cloud-based solution.
Summary
The Oracle Autonomous Database is a groundbreaking solution that seamlessly combines the flexibility of cloud computing with the power of machine learning. It offers a fully automated service, accommodating diverse data types and supporting various workloads with a converged engine. Available on Oracle Cloud Infrastructure (OCI) for serverless or dedicated deployments, as well as on-premises with Oracle Exadata Cloud@Customer and OCI Dedicated Region, it ensures high performance, availability, and security. The foundation includes Oracle Database Enterprise Edition, Exadata Database Machine, Oracle Cloud Infrastructure, best practices, and machine learning. Autonomous Database comes in two editions—Autonomous Data Warehouse (ADW) for analytics and data warehousing, and Autonomous Transaction Processing (ATP) for transactional and mixed workloads. It can be deployed on Serverless or Dedicated Exadata Infrastructure, each offering unique benefits. Serverless is perfect for quick scaling and pay-as-you-go usage, making it ideal for line-of-business applications and sandbox environments. On the other hand, Dedicated Infrastructure provides users with their private database cloud within the Oracle Public Cloud, offering customization options for operational policies and serving as an excellent choice for a comprehensive cloud-based solution.
Learn more about Oracle’s Autonomous and database consolidation thru the references and links below.
https://www.oracle.com/autonomous-database/
https://www.oracle.com/a/ocom/docs/database/oracle-autonomous-database-strategy-wp.pdf
https://blogs.oracle.com/database/post/a-guide-to-why-and-how-to-consolidate-databases
Author – (Gupta, Divit, n.d.)