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Next-Gen Data Management with Oracle Database 23ai
Oracle office, Orlando, FL
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What will we discuss?
Oracle Database 23ai: Innovation Redefined
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AI and Machine Learning Integration
With automated Machine Learning (AutoML), the development and deployment of machine learning models are simplified directly within the database. Provide advanced analytics and predictive insights with built-in AI capabilities.
Developer-Friendly Functionalities
Access robust APIs and tools for developers to build and deploy applications efficiently. Oracle Database 23ai facilitates continuous integration and continuous deployment (CI/CD) for database applications.
Multi-Model Database Support
Seamless management of diverse data types, including relational, JSON, XML, and spatial data, within a single platform, enhancing flexibility and efficiency in data handling.
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Enhanced User Experience
Discover a more intuitive and user-friendly interface for database administrators and users. It provides personalized dashboards that enable users to create custom dashboards to monitor and manage their data environments.
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See The Team In Action
Upcoming Events
- AI for ERP
- JD Edwards
- Agentic AI
AI for JD Edwards
- AI for Higher Education
- AI for ERP
- IT Leadership
- Administrative Transformation
- HEUG Alliance 2026
AI for Higher Education
Key Functionalities
Powerful Features of Oracle Database 23ai
A converged database to manage mission-critical workloads effectively with the power of AI and Machine Learning.
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AI Vector Search:
Leverage AI vector search for application development, utilizing next-generation AI models to generate and store vectors efficiently. -
JSON Relational Duality:
Seamlessly integrate and query JSON data within relational databases, bridging the gap between structured and unstructured data. -
JavaScript Stored Procedures:
Write and execute stored procedures using JavaScript directly within the database, enhancing flexibility for developers. -
JSON Schemas:
Define schemas for JSON documents to ensure data integrity and facilitate validation.
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Property Graphs:
Model and query graph data structures within the database, enabling advanced graph analytics. -
Data Use Case Domains:
Utilize predefined data models tailored to specific industry use cases for rapid deployment and efficient data management. -
Schema Annotations:
Incorporate metadata into database schemas for improved organization and management. -
Resources:
Access up to 2 CPUs for foreground processes, 2 GB of RAM, and 12 GB of user data storage on disk.
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Latest Functionality
Oracle AI Vector Search: Bridging AI and Data Retrieval
This advanced feature leverages new-generation AI models to generate and store vectors, enabling highly efficient and accurate data retrieval.
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Unified Database Simplicity: Effortlessly integrate similarity search with relational, text, JSON, spatial, and graph data types within a single database to enhance your applications.
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Natural Language Interaction with Business Data: Enable natural language search across your private business data using RAG to guide the LLM of your choice for more intuitive interactions.
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Develop Customized AI Apps: Utilize your preferred development tools, AI frameworks, and languages to create AI applications tailored to your needs.
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Enterprise-Grade AI: Easily build mission-critical AI applications with industrial-strength capabilities, ensuring scalability, performance, high availability, and security.
See The Team In Action
Upcoming Events
- AI for ERP
- JD Edwards
- Agentic AI
AI for JD Edwards
- AI for Higher Education
- AI for ERP
- IT Leadership
- Administrative Transformation
- HEUG Alliance 2026
AI for Higher Education
See The Team In Action
Upcoming Events
- AI for ERP
- JD Edwards
- Agentic AI
AI for JD Edwards
- AI for Higher Education
- AI for ERP
- IT Leadership
- Administrative Transformation
- HEUG Alliance 2026