I previously described how Oracle had positioned its database portfolio to address any and all data platform requirements. The caveat to that statement at the time was that any organization wanting to take advantage of the company’s flagship Oracle Autonomous Database could only do so using Oracle Cloud Infrastructure (OCI) cloud computing service, their own datacenter or a hybrid cloud environment. The widespread popularity of Oracle Database and the advanced automation capabilities delivered by Oracle Autonomous Database have been significant in helping Oracle establish itself as a hyperscale cloud provider, as has its investment in differentiating cloud services, and its competitive scalability, reliability and performance capabilities. Oracle’s partnership with Microsoft to deliver database services via Azure was a significant development, even amongst a slew of announcements from Oracle related to generative AI.
Founded in 1977, Oracle was a dominant force in the early years of database management systems before expanding its focus through a combination of research and development and acquisitions to address applications and infrastructure, both on-premises and in the cloud. Although Oracle has long since expanded its addressable market beyond databases, the widespread adoption of Oracle Database means that it remains a critical component of the company’s overall portfolio. Oracle was rated Exemplary in Ventana Research’s 2023 Data Platforms Buyer’s Guide. Oracle has enhanced Oracle Database over the years by expanding beyond the relational model to a multi-model database with support for non-relational data types, including spatial and graph objects as well as the JSON document format. Oracle Autonomous Database is a managed service based on Oracle Database that also leverages machine learning to automatically optimize, scale, tune, patch and secure the database management system. Described as a converged database offering, Oracle Autonomous Database is optimized for transaction processing and mixed workloads (Autonomous Transaction Processing) or analytic workloads (Autonomous Data Warehouse). It can also be provisioned to address JSON data processing requirements in the form of Autonomous JSON Database.
Until recently, Oracle Autonomous Database was only available on OCI in shared or dedicated deployments, in a customer’s own datacenter via Exadata Cloud@Customer or Dedicated Region Cloud@Customer and in hybrid cloud environments. That changed with the recent expansion of Oracle’s relationship with Microsoft to deliver Oracle Database@Azure, which provides access to services running on OCI deployed in Microsoft Azure datacenters, including Oracle Exadata Database services, Oracle Autonomous Database services and Oracle Real Application Clusters (RAC). The announcement builds on the previous launch of Oracle Database Service for Microsoft Azure, which enabled Azure users to provision and manage Oracle database running in Oracle datacenters. Both offerings are designed to provide a long-term cloud migration pathway for enterprises running Microsoft applications on Oracle Database by facilitating the adoption of Azure cloud services and avoiding the need for customers to choose between Azure and OCI.
The announcement of Oracle Database@Azure served as an appetizer for a plethora of data and analytics announcements made by Oracle at its Cloud World customer event in September. Many of the announcements focused on generative AI, including the beta launch of OCI Generative AI service. Created in conjunction with language AI specialist Cohere, the OCI Generative AI service provides API-based access to Cohere’s text generation, text summarization and text representation large language models (LLMs), facilitating integration by developers into their applications. Oracle is utilizing OCI Generative AI service itself for the new AI capabilities being added to Oracle Analytics Cloud, including natural language interaction, recommendations, summarization and document understanding. It will also use the service to embed generative AI services in its SaaS applications, such as Oracle Fusion Cloud Applications Suite, Oracle NetSuite and Oracle Cerner.
OCI Generative AI service is also designed to work with the newly announced AI Vector Search features of Oracle Database 23c, which enable the semantic content of documents,
In addition to bringing generative AI to the database, Oracle also articulated how it facilitates a more flexible approach to data usage by bringing the broader concepts of automated generation and declarative intent to data usage. While the company’s approach is in the early stages, this is being delivered in Oracle Database by enabling the generation of multiple views of data stored in the relational database depending on how the application developer intends the data to be used. Specifically, JSON Relational Duality views enable Oracle Database to generate the JSON document format and APIs from relational tables to expose data to multiple JSON document-based applications without data duplication. Oracle Database 23c also includes property graph views, enabling developers to declare relational tables to be viewed as vertices and edges for graph navigation and analysis. Oracle has only scratched the surface of how this concept of declarative intent will shape how enterprises make use of the data stored in its databases. I anticipate we will be hearing more about this approach in 2024. In the meantime, I recommend that all organizations exploring their options for data platforms include Oracle in their evaluations.
Regards,
Matt Aslett