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Duration 14 hours
Course Outline
1. Introduction and What's New in Oracle Database 23ai
- Overview of the release, its market positioning, and the developer-centric roadmap.
- A high-level exploration of AI Vector Search, JSON/relational duality, and async drivers.
- An analysis of how 23ai transforms standard developer workflows and application patterns.
2. Getting Hands-on: Environment and Tools (Lab)
- Installation and utilization of Oracle Database 23ai Free for laboratory exercises.
- Configuration of JDK, IDE, and client drivers (including JDBC and R2DBC where applicable).
- Establishing the first connection, executing simple queries, and scaffolding a sample project.
3. JSON Relational Duality and New Data Types (Lab)
- Application of the improved JSON data type and JSON collections in code.
- Understanding duality patterns: determining when to prioritize relational versus JSON approaches.
- Practical examples: storing, querying, and updating JSON objects from Java/Quarkus applications.
4. AI Vector Search and Developer Use Cases (Lab)
- Introduction to AI Vector Search, including vector data types and vector indexes.
- Constructing a semantic-search example: covering embedding generation, storage, and similarity queries.
- Integrating Vector Search with application code and libraries (with conceptual discussion of LangChain/LlamaIndex examples).
5. Asynchronous Programming, Pipelining, and Performance Patterns
- Comprehending driver-level pipelining and async request patterns for JDBC, R2DBC, and other drivers.
- Exploring client-side patterns (such as reactive streams and Java virtual threads) and their server-side impact.
- Practical lab: implementing pipelined calls to measure and verify throughput improvements.
6. SQL, PL/SQL Enhancements, and Security Controls
- Review of new SQL/PLSQL language features relevant to developers (e.g., schema annotations, direct joins in updates, and the new Boolean type).
- An overview of SQL Firewall and its role in enhancing the runtime security of executed SQL.
- Hands-on exercise: migrating a small procedure to utilize new language features and testing SQL Firewall behavior in a controlled lab setting.
7. Testing, Debugging, and Deployment Best Practices (Lab)
- Unit testing database logic, generating representative test data, and measuring behavior with new features.
- Packaging and deploying developer applications that leverage 23ai features to test environments.
- Checklist: covering performance tuning, compatibility considerations, and next steps for production readiness.
Summary and Next Steps
Requirements
- A solid grasp of SQL and relational database concepts.
- Practical experience with application development in Java or comparable languages.
- Basic familiarity with PL/SQL or server-side scripting concepts.
Target Audience
- Application developers working with Java, Quarkus, or similar technologies.
- Database developers and PL/SQL engineers.
- DevOps engineers overseeing developer tooling and CI environments.
Testimonials (1)
good explanation on each points and provide assignment for practices.
