Integration Patterns
Patterns for connecting disparate systems reliably — from simple point-to-point integrations to enterprise-scale transformation and routing pipelines.
Enterprise Service Bus (ESB)
Centralized mediation, transformation, and routing for legacy enterprise integration.
Canonical Data Model
A shared normalized format reducing transformation complexity across many integrated systems.
Anti-Corruption Layer
Protecting a domain from external model leakage when integrating with legacy systems.
Change Data Capture (CDC)
Propagating database changes as events for near-real-time data synchronization.
ETL vs ELT
Comparing transform-before-load vs load-before-transform for data pipeline design.
Data Synchronization
Keeping data consistent across multiple systems with conflict resolution strategies.
Orchestration vs Choreography
Central workflow control vs decentralized event flows for multi-step business processes.
File-Based Integration
Exchange through files, drop zones, and object storage when partner constraints require batch delivery.
Batch Integration
Periodic large-volume data exchange between systems — patterns, scheduling, and error handling.
Streaming Integration
Real-time data flow integration using Kafka, Kinesis, or Pulsar as the integration backbone.