MongoDB Event-Driven Architecture

Event-Driven Architecture Pattern Comparison

Event Streaming & Processing Implementation

Compare how MongoDB and PostgreSQL handle event-driven architectures, examining real-time event detection, event storage, and service decoupling approaches.

🔍 Key Event Architecture Differences

MongoDB's Change Streams provide native event streaming from data changes, while PostgreSQL requires external tools and message brokers for similar event-driven capabilities.

🍃 MongoDB Event-Driven Architecture

Native Change Streams: MongoDB provides built-in real-time event streams from any data change, eliminating the need for external message brokers or complex trigger systems.

Change Streams: Real-time event detection from any data mutation
Event Store: Natural document storage for complex event payloads
Guaranteed Ordering: Resume tokens ensure no events are missed
Loose Coupling: Services react to data changes automatically
Unified Platform: Event store and application database combined

Built-in Events

Native change streams eliminate external tools

🐘 PostgreSQL Event-Driven Architecture

External Event Infrastructure: PostgreSQL requires triggers, WAL-based tools like Debezium, or message brokers to achieve event-driven patterns.

ACID Events: Strong consistency for event transactions
Trigger Support: Database triggers for event creation
WAL Streaming: Write-ahead log for change capture
Message Integration: Works with external event systems
SQL Processing: Complex event queries and analysis

PostgreSQL Database

Application Tables

Event Table

External Event Infrastructure

Debezium

Kafka

RabbitMQ

Multiple external tools required for event streaming

External Dependencies

Requires message brokers and change data capture tools

⚡ Event-Driven Implementation Comparison

MongoDB Advantages:

• Built-in Change Streams for real-time events
• No external message brokers needed
• Resume tokens prevent missed events
• Single platform for events and data

PostgreSQL Challenges:

• Requires external tools (Debezium, Kafka)
• Complex trigger-based event generation
• Additional infrastructure to manage
• Event ordering and delivery guarantees