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Introducing Oracle Database 23ai

AI for Data. AI for Devs. AI where you need It.


Oracle Database 23ai provides new capabilities that make it simple for developers and data professionals to power apps, application development, and mission critical workloads with AI.

Sample applications

A few application examples built with database technologies, to get you started on your simplified app dev journey.

Cloud Banking

A modern cloud-native banking application that combines mobile and web interfaces, unifying banking, insurance, credit, investments, mortgages built with the Oracle Backend for Spring Boot. This shows the app and data workflows with Visual Studio Code, Spring starters, and VS-code extensions to fit in your current dev environment.

Retail store e-shop

e-shop is a web-based, ecommerce retail application example, developed to demonstrate OLTP and analytics in a massively parallel processing (MPP) architecture.

Marketing Personalization and Analytics

Modern data platforms require analytics across storage engines (relational, object storage, and others) and data types. Oracle Autonomous Database captures tabular, spatial, graph, and JSON data and includes specialized algorithms for each of these data types. Oracle MovieStream—a fictitious online movie streaming company—is used to illustrate how different types of sophisticated analytics can be applied to both structured and unstructured data.

Mobile food delivery

Build a mobile food delivery app with a data-centric architecture pattern using Kubernetes engine, Docker containers, and Oracle Autonomous Database. Modern AppDev is synonymous with data-driven microservices generating operational data and code events, and it incorporates artificial intelligence (AI) and/or machine learning (ML).

Online shopping cart

This sample application creates a shopping cart from scratch using Oracle Autonomous Database and Oracle APEX. First, a sample dataset is imported, and then an app is built with pages, such as dashboard, products, and multiple reports.

Fraud detection

This sample application shows how a data professional can build a machine learning–driven insurance app with APEX, starting with data preparation and finishing up with the successful deployment of a machine learning model.

Modern application development

Modern application development with the Oracle Database covers various technologies that have been integrated in the sample applications and are used to build powerful enterprise applications.

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Applications developed with the Oracle Database can be built in all the popular languages – Java, Javascript, Python, SQL, PL/SQL, C/C++, .NET among many others.

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Microservices and mobile

Microservices are bounded contexts with loose coupling, similar to domain driven design, but built on the modern stack of Containers, Kubernetes, and the converged Oracle Database. Mobile APIs with Parse, further help unify web-first and mobile-first projects.

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Application services

Microservices are bounded contexts with loose coupling, similar to domain driven design, but built on the modern stack of Containers, Kubernetes, and the converged Oracle Database. Mobile APIs with Parse, further help unify web-first and mobile-first projects.

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Data types

Intelligent applications unify both structured and unstructured data to run operations or perform business analytics. Oracle Database brings all data types in an operational scalable database significantly improving operations agility, data security, DevOps, and DataOps capabilities.

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Containers, Kubernetes, Backend platform for Spring, Transaction managers, CI/CD pipelines, unified observability are all important to simplify DevOps with multi-cloud deployments.

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SQL remains the most powerful database tool, and there are several ways to make the use of SQL easy and powerful at the same time. Low code tools like APEX hide SQL by providing UI driven interfaces for application development, i.e. low-code.

What do you want to develop?

Tell us what kind of app you want to put together and we’ll point you in the right direction.

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An intelligent business app using ML to discover insights

Many applications need the use of analytics or machine learning to make decisions or to present summaries of results. Machine learning is built into the Oracle Database, and many pre-trained ML models are available to run in the database or can be imported using ML services. This use case recommends food and wine pairing by analyzing food reviews and wine reviews, looking at the descriptions of each food and wine, and extracting a taste/flavor vector from the text and matching them, using a ML model word2vec with the Oracle Database.

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A gaming app using Flutter

Flutter is a popular language for mobile apps and for building games. An app to enter gamescores shows the flexibility of using a Backend Platform for mobile/gaming apps.

See user authentication and creating/getting documents. More info for indexing, schema creation and validation rules, associating ACLs with a user so they only see their gamescores, GraphQL can be added for a fuller gaming development experience.

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Consolidating personal finances on the Cloud with Spring Boot

An application for personal banking, insurance payments, credit card management, investments is built using Spring Boot, and a mobile app is shown to interact with it. A backend platform runs the app containers alongside the Oracle Database which is used for data operations.

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Cloud-native app for food delivery

Build GrabDish a food delivery app within an hour. Order food, find recommendations to pair a wine with the food, and get it delivered with a map of a route for the delivery service. These microservices are in app containers managed by Kubernetes, and use the Oracle Database built-in messaging for communication.

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Extended Reality (XR) based apps for Healthcare

Using a Hololens 2 or Oculus devices doctors can see patients information more holistically. Develop healthcare use cases with the Oracle Database with AI, messaging, graph technologies in the database cloud.

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Robust fraud detection solutions – auto insurance fraud detection

Oracle Machine Learning notebooks working in conjunction with automobile insurance claims investigators is a two-step process. First, Oracle Machine Learning “flags” for the investigator anomalous insurance claims using an unsupervised learning algorithm (1-Class Support Vector Machine). Then the claims investigators focus on the most suspicious claims using their expertise and knowledge using an Oracle APEX application.

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Personalized ads and recommendations for movies

Using Graph analytics to recommend movies, model your data as a graph, and run graph algorithms on your data. Graph algorithms analyze your data based on the connections and relationships in your data. Graph queries find patterns in your data, such as cycles, paths between vertices, anomalous patterns, and so on. Find movies your friends liked.

Developer week

A cross-platform game in Unity

Unity is a cross-platform game engine developed by Unity Technologies, first announced and released in June 2005 at Apple Worldwide Developers Conference as a Mac OS X game engine. The engine has since been gradually extended to support a variety of desktop, mobile, console, and virtual reality platforms. The Parse Platform is a back-end for mobile developers, open-sourced by Facebook/Meta in 2016, that helps to store data in the cloud, manage identity log-ins, handle push notifications, and run custom code in the cloud. Parse has a unity SDK for game development and a simple – Rock, Paper, Scissors game is shown as an example to get you started.