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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 tour of AI Vector Search, JSON/relational duality, and asynchronous drivers.
  • How 23ai transforms typical developer workflows and application patterns.

2. Getting Hands-on: Environment and Tools (Lab)

  • Installation and configuration of Oracle Database 23ai Free for laboratory use.
  • Setting up the 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)

  • Utilizing the improved JSON data type and JSON collections within application code.
  • Understanding duality patterns: determining when to use 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, vector data types, and vector indexing.
  • Building a small-scale semantic search example, covering embedding generation, storage, and similarity queries.
  • Integrating Vector Search with application code and libraries (with conceptual discussions on LangChain and LlamaIndex).

5. Asynchronous Programming, Pipelining, and Performance Patterns

  • Understanding driver-level pipelining and asynchronous request patterns for JDBC, R2DBC, and other drivers.
  • Examining client-side patterns (such as reactive streams and Java virtual threads) and their impact on the server.
  • Practical lab: implementing pipelined calls to measure and improve throughput.

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

  • Exploring new SQL/PLSQL language features relevant to developers, such as 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 environment.

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 for performance tuning, compatibility considerations, and next steps for production readiness.

Summary and Next Steps

Requirements

  • A solid 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 principles.

Audience

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

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