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Oracle Corporation
10/02/2024 | Press release | Distributed by Public on 10/01/2024 21:49
Take advantage of Oracle Database 23ai innovations with Autonomous ...
You might know the Autonomous Database as an Oracle Database, which runs on Exadata Cloud Infrastructure, providing optimized performance, security, resource efficiency, availability, and more. But did you know that Autonomous Database now supports Oracle Database 23ai? You get all the benefits of Oracle Database 23ai, the latest long-term support release of the Oracle Database with more than 300 new features, with the same self-driving, self-securing, self-repairing database that you know and love. Now, let's get into the innovations you can take advantage with Oracle Autonomous Database on Oracle Database 23ai.
Oracle Database 23ai benefits
Features and components of Oracle Database of 23ai.
Figure 1: Oracle Database 23ai feature highlights
Oracle Database 23ai focuses on AI and developer productivity because we created it with developers in mind. Oracle's vision for this release is to make modern applications and analytics easy to generate and run for all use cases at any scale, delivering a complete and simple platform for all your data management needs. We're revolutionizing our converged database technologies to unify data models, such as JSON, graph, and relational, at a more fundamental level. While it's already a multimodal, multi-workload, multitenant platform that supports all data types and applications for different workload profiles, we're adding more features to simplify application development. So, you get more tools to innovate simpler and faster, all in a single platform.
One of the key features to come out of Oracle Database 23ai is JSON Relational Duality, which provides the benefits of both relational tables and JSON documents, without the limitations of either model. With JSON Relational Duality, data is stored in relational tables but is accessed seamlessly by applications in the form of JSON documents. You can retrieve and store all the data for a single app-tier object in one database operation, making it simple and flexible for developers, you can manipulate documents in ways that you're used to without having to worry about the underlying relational structure. For a demonstration, see JSON Relational Duality Views.
You also get Operational Property Graph, which simplifies advanced capabilities for handling graph data, empowering users to model, query, and analyze complex relationships with greater efficiency. You can use SQL instead of PGQL to perform graph modeling and analytics, making it easier for you. With native support for the new SQL:2023 standard, it enables you to perform robust graph analytics that integrate with other data types using simple SQL syntax. This integration enhances the ability to manage interconnected data and extract valuable insights in real-time applications. For more information, see Get started with property graphs in Oracle Database 23c Free - Developer Release.
RAG with AI Vector Search
Another new feature, AI Vector Search is a breakthrough technology that enables searching for documents, images, patterns, and data that have similar content. Imagine that you want to know which feature to add to your product. When you ask a large language model (LLM), generative AI (GenAI) will take your question and access available knowledge to give you an answer. That answer is more theoretical based on common patterns that GenAI pulls from the data it was trained on. That's why you need AI Vector Search to improve GenAI by augmenting your prompts with private database content. This way, you can get better answers and avoid training LLMs on sensitive private data.
When you combine retrieval-augmented generation (RAG) with AI Vector Search, you get the best of both worlds: Real-time retrieval of live data and AI-powered analysis. You can directly pull your company's real data, including usage statistics, feature requests, and customer feedback. So, you get data-driven insights that are more actionable, offering specific features that you can prioritize based on actual metrics, user behavior, and competitive analysis in real time. For more information on Oracle AI Vector Search, see our demo and documentation.
An example interaction with an LLM chatbot.
Figure 2: Example of asking an LLM Chatbot
An example interaction with a chatbot enhanced by RAG with AI Vector Search.
Figure 3: Example of asking an LLM Chatbot enhanced by RAG with AI Vector Search
Now let's think about the possibilities on a larger, enterprise scale. When you combine RAG with AI Vector Search, you can help consumers find what they're looking for with improved accuracy, which can lead to better customer experiences and potential purchases. You can also use it to solve your business problems more efficiently and accurately. With Oracle Database 23ai, you don't need to move and synchronize vector data, manage multiple products, and so on because you can combine both business data and vectors when answering your questions in a single database. To get the full effect of how amazing these features are, see the Oracle Database documentation.
Autonomous Database and Oracle Database 23ai
You get all the Oracle Database 23ai benefits we've talked about with the benefits of the fully managed Autonomous Database, with up to 99.995% SLA. With Autonomous Database, you can streamline Oracle's data management process to organize and analyze your data more efficiently, making it easier to discover patterns and insights that might have previously been hidden.
With Select AI, currently only available on Autonomous Database, you can use natural language questions to query data and get responses using generative AI. So, you can generate SQL specific to your database using questions like, "what are the top consuming customers for my product," or "what was the largest revenue generating product in FY24Q3?" You can easily access LLMs from multiple providers with easy-to-use SQL APIs. Plus, you can build applications that lets your users get answers from their data using natural language processing (NLP) without SQL, democratizing your data to everyone in your company. For more information and a demonstration, see Natural Language Interaction with Data Using Autonomous Database Select AI, and the documentation.
Select AI can make your life easier, and industry experts are impressed by Autonomous Database. Carl Olofson, research vice president of Data Management Software at IDC, said, "With Autonomous Database giving users an enterprise view of an organization's data and Select AI providing a natural language interface with wide-ranging SQL translation and generation capabilities, you have a differentiated combination that pushes the boundaries of data interaction to new levels."
Try Autonomous Database with Oracle Database 23ai for yourself!
Oracle Database 23ai on Autonomous Database offers efficiency, productivity, and flexibility for your application development with mission-critical security, scalability, and reliability, enabling you to innovate faster with better insights. Try it out yourself and see how it meets your ever evolving needs of modern applications and provides a platform for innovation and efficiency in data-driven enterprises. Share your Autonomous Database solutions on LinkedIn with us by using #InnovateWithADB. We can't wait to see what you create!
Get started with Autonomous Database
Autonomous Database Serverless - Oracle Database 23ai support documentation
Autonomous Database on Dedicated Exadata Infrastructure with Oracle Database 23ai Support - Technical Documentation
Oracle.com Oracle Database 23ai
The Future of App Development Using New AI Innovations in Autonomous Database
Generative Data Dev and App Dev - Juan Loaiza, Oracle EVP - Oracle CloudWorld 2024