Introduction

Oracle GoldenGate 23ai is a real-time data integration and replication platform designed to enable high-speed, low-latency data movement across heterogeneous systems. It supports modern event-driven architectures and streaming data pipelines, making it ideal for building scalable, resilient, and real-time data-driven applications. In this training, learners will focus on leveraging GoldenGate 23ai for data streaming and event-driven processing to support modern analytics, microservices, and cloud-native architectures.

Learner Prerequisites

• Basic understanding of databases and SQL concepts
• Familiarity with data integration or ETL/ELT processes
• Knowledge of distributed systems or messaging systems (preferred)
• Understanding of cloud or microservices architecture (basic level)
• Exposure to Oracle Database or similar RDBMS systems (recommended)

 Table of Contents

1. Introduction to Event-Driven Architecture with GoldenGate 23ai

1.1 Fundamentals of Event-Driven Systems
1.2 Role of GoldenGate in Real-Time Data Streaming
1.3 Core Components of GoldenGate 23ai Architecture
1.4 Use Cases in Modern Data Ecosystems

2. GoldenGate 23ai Architecture for Streaming Data

2.1 Microservices-Based Architecture Overview
2.2 Capture, Pump, and Delivery Mechanisms
2.3 Trail Files and Event Capture Flow
2.4 Integration with Messaging Systems

3. Setting Up GoldenGate 23ai for Real-Time Streaming

3.1 Installation and Environment Configuration
3.2 Creating Extract Processes for Data Capture
3.3 Configuring Replicat for Target Systems
3.4 Verifying Initial Data Flow

4. Event Capture and Change Data Capture (CDC) Mechanism

4.1 Understanding CDC in GoldenGate
4.2 Transaction Log-Based Capture
4.3 Filtering and Transformation of Events
4.4 Handling High-Volume Data Streams

5. Real-Time Data Replication and Streaming Pipelines

5.1 Building End-to-End Streaming Pipelines
5.2 Data Routing and Delivery Strategies
5.3 Multi-Target Replication Scenarios
5.4 Latency Optimization Techniques

6. Integration with Kafka and Event Streaming Platforms

6.1 GoldenGate Kafka Adapter Overview
6.2 Publishing Events to Kafka Topics
6.3 Consuming GoldenGate Streams in Microservices
6.4 Event-Driven Processing Workflows

7. Transformation and Filtering in Streaming Pipelines

7.1 Data Mapping and Transformation Rules
7.2 Event Filtering Techniques
7.3 Enrichment of Streaming Data
7.4 Handling Schema Changes in Real Time

8. Performance Optimization for Streaming Workloads

8.1 Tuning Extract and Replicat Processes
8.2 Memory and Throughput Optimization
8.3 Managing Latency in High-Speed Environments
8.4 Best Practices for Scalability

9. Monitoring, Logging, and Troubleshooting

9.1 Monitoring GoldenGate Streams
9.2 Using Performance Metrics and Reports
9.3 Common Errors and Resolutions
9.4 Alerting and Auditing Strategies

10. Security in Event-Driven Data Streaming

10.1 Data Encryption in Transit and At Rest
10.2 Access Control and Authentication
10.3 Secure Configuration of Streaming Pipelines
10.4 Compliance and Governance Considerations

11. High Availability and Fault Tolerance in Streaming Systems

11.1 Active-Active and Active-Passive Configurations
11.2 Recovery Mechanisms in GoldenGate
11.3 Ensuring Data Consistency During Failures
11.4 Disaster Recovery Strategies

12. Real-World Use Cases and Industry Applications

12.1 Real-Time Analytics Pipelines
12.2 Financial Transaction Streaming
12.3 IoT and Sensor Data Processing
12.4 Microservices Event Synchronization

Conclusion

Understanding Data Streaming and Event-Driven Architecture using GoldenGate 23ai enables organizations to build highly responsive, scalable, and real-time data systems. This training equips learners with practical skills to design, implement, and optimize modern streaming pipelines for enterprise-grade applications.