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Duration 14 hours
Course Outline
1. Introduction and Key Innovations in Oracle Database 23ai
- Overview of the release, its market positioning, and the developer-focused roadmap.
- Brief exploration of AI Vector Search, JSON/relational duality, and asynchronous drivers.
- Impact of 23ai on standard developer workflows and application design patterns.
2. Practical Setup: Environment and Tooling (Lab)
- Installation and configuration of Oracle Database 23ai Free for laboratory exercises.
- Setup of JDK, IDE, and client drivers (including JDBC and R2DBC where relevant).
- Establishing initial connections, executing basic queries, and scaffolding a sample project.
3. JSON Relational Duality and Enhanced Data Types (Lab)
- Utilizing the upgraded JSON data type and JSON collections within application logic.
- Duality strategies: determining when to favor relational versus JSON approaches.
- Practical examples: storing, retrieving, and modifying JSON objects via Java/Quarkus applications.
4. AI Vector Search and Developer Applications (Lab)
- Fundamentals of AI Vector Search, vector data structures, and vector indexing.
- Constructing a semantic search prototype: handling embedding generation, storage, and similarity lookups.
- Integrating Vector Search with application code and libraries (conceptual discussion of LangChain/LlamaIndex).
5. Asynchronous Programming, Pipelining, and Performance Optimization
- Understanding driver-level pipelining and asynchronous request patterns for JDBC, R2DBC, and other clients.
- Client-side implementation patterns (reactive streams, Java virtual threads) and their impact on server resources.
- Practical exercise: implementing pipelined calls and benchmarking throughput gains.
6. SQL, PL/SQL Improvements, and Security Mechanisms
- Relevant new SQL/PLSQL language features for developers (e.g., schema annotations, direct joins in updates, native Boolean type).
- Overview of SQL Firewall and its role in strengthening runtime SQL security.
- Hands-on task: refactoring a small procedure to leverage new features and verifying SQL Firewall behavior in a controlled lab setting.
7. Best Practices for Testing, Debugging, and Deployment (Lab)
- Unit testing database logic, creating representative test datasets, and assessing behavior with new features.
- Packaging and deploying 23ai-enabled developer applications to test environments.
- Readiness checklist: performance tuning, compatibility checks, and pathways to production deployment.
Wrap-up and Future Directions
Requirements
- Solid comprehension of SQL and relational database principles
- Practical experience in application development using Java or equivalent languages
- Basic familiarity with PL/SQL or server-side scripting concepts
Target Audience
- Application developers working with Java, Quarkus, or similar frameworks
- Database developers and PL/SQL specialists
- DevOps engineers overseeing developer tooling and CI/CD environments
Testimonials (1)
good explanation on each points and provide assignment for practices.
