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Course Outline

1. Introduction and Updates in Oracle Database 23ai

  • Overview of the release, positioning, and developer-centric roadmap.
  • High-level exploration of AI Vector Search, JSON/relational duality, and async drivers.
  • How 23ai transforms typical developer workflows and application patterns.

2. Hands-on Environment and Tools Setup (Lab)

  • Installing and configuring Oracle Database 23ai Free for lab exercises.
  • Setting up the JDK, IDE, and client drivers (JDBC, R2DBC where applicable).
  • Establishing the first connection, running simple queries, and creating a sample project scaffold.

3. JSON Relational Duality and New Data Types (Lab)

  • Leveraging the improved JSON data type and JSON collections in application code.
  • Understanding duality patterns: determining when to use relational versus JSON approaches.
  • 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 indexes.
  • Building a semantic-search example: embedding generation, storage, and similarity queries.
  • Integrating Vector Search with application code and libraries (conceptual discussion of LangChain/LlamaIndex examples).

5. Asynchronous Programming, Pipelining, and Performance Patterns

  • Understanding driver-level pipelining and async request patterns for JDBC, R2DBC, and other drivers.
  • Client-side patterns (reactive streams, Java virtual threads) and their impact on the server.
  • Practical lab: Implementing pipelined calls and measuring throughput improvements.

6. SQL, PL/SQL Enhancements, and Security Controls

  • Exploring new SQL/PLSQL language features relevant to developers (e.g., schema annotations, direct joins in updates, new Boolean type).
  • Overview of SQL Firewall and its role in enhancing runtime SQL security.
  • Hands-on: Migrating a small procedure to utilize new language features and testing SQL Firewall behavior in a controlled lab.

7. Testing, Debugging, and Deployment Best Practices (Lab)

  • Unit testing database logic, generating representative test data, and evaluating behavior with new features.
  • Packaging and deploying developer apps utilizing 23ai features to test environments.
  • Checklist: Performance tuning, compatibility considerations, and next steps for production readiness.

Summary and Next Steps

Requirements

  • Understanding of SQL and relational database concepts
  • Experience in application development using Java or similar languages
  • Familiarity with basic PL/SQL or server-side scripting concepts

Audience

  • Application developers (Java, Quarkus, or similar)
  • Database developers and PL/SQL engineers
  • DevOps engineers responsible for developer tooling and CI environments
 14 Hours

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