Making AI the Centerpiece of a New-Look App Development Industry

Oracle has officially confirmed general availability of its new converged database called Oracle Database 23ai. According to certain reports, the stated database is essentially conceived to simplify the use of AI with data, accelerate app development, and more effectively run mission-critical workloads. This it is able to do by bringing AI algorithms to where the data lives, instead of having to move the data to where the AI algorithm lives. The maneuver, on its part, ensures that AI can run in real-time across Oracle databases, and therefore, improve the effectiveness, efficiency, and security ofoperations. Talk about the whole value proposition on a slightly deeper level, it begins with a Oracle AI Vector Search functionality, which simplifies the process of searching documents, images, and relational data based on their conceptual content rather than specific words, pixels, or data values. Next up, we must get into the solution’s Oracle Exadata System Software 24ai. In essence, the Exadata software comes bearing an ability to accelerate AI Vector Search by up to orders of magnitude. Such functionality enables different applications to run AI Vector Search for both large volumes of data and high numbers of users. Then, there is OCI GoldenGate 23ai, which can effectively facilitate heterogeneous data integration and high availability across cloud data stores. To be more specific, this particular feature delivers capabilities that allow vectors to be replicated in real-time across heterogeneous vector stores.

Moving on, in a push towards accelerating app development, Oracle Database 23ai further presents you with a prospect of JSON Relational Unification. From a practical standpoint, JSON Relational Duality addresses the mismatch between how some applications want to use data versus how relational databases store data. This translates to the solution’s knowhow in helping users easily retrieve and store the same data using REST or native JSON APIs. These users can also do the same without compromising data consistency, storage efficiency, and flexibility inherent in the relational data model. Joining the same is Graph Relational Unification, where you have Operational Property Graph empowering developers to easily build applications that navigate the connections between and within data using property graph queries. Another detail worth a mention here talks to how Property Graph queries can run on top of all types of data supported by Oracle Database, including relational data, JSON data, and spatial data.

Hold on, we still haven’t touched on the new solution’s take on mission-critical data. This particular take keepsOracle Globally Distributed Database with RAFT at the heart of everything, something which allows for data in the cloud to be stored across multiple physical databases in well-diversified locations. Such a mechanism helps users to achieve hyperscale and address those data residency and data sovereignty requirements. As for the RAFT part, the replication of it between physical databases enables automatic failover with zero data loss in single digit seconds. A capability of this sort can go a long distance especially when the agenda is to build cloud-scale distributed databases that must achieve ultra-high scalability and availability. Finally, we have Oracle True Cache, which is an in-memory, always consistent, application transparent, high-performance middle-tier cache, capable of improving application response times, as well as reduce the load on database servers. 

“Oracle Database 23ai is a game changer for enterprises worldwide, and because of the importance of the breakthrough AI technology in this release, we are renaming it to Oracle Database 23ai,” said Juan Loaiza, executive vice president of Mission-Critical Database Technologies at Oracle. “AI Vector Search combined with new unified development paradigms and mission-critical capabilities makes it simple for developers and data professionals to build intelligent apps, increase developer productivity, and run mission-critical workloads.”

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