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From CRUD to Real-Time Analytics: Why Business Events Matter
Many operational systems (e.g. SaaS platforms and transactional systems) are built around CRUD operations and batch processing, but these approaches often fall short when businesses demand real-time insights. A common intermediate step is Change Data Capture (CDC), which reflects changes at the database level in near-real time. However, CDC primarily captures raw data changes (e.g., inserts, updates, deletes) and doesn’t provide the context of what those changes mean in the real world. For example, CDC might log an update to a database row, but it doesn’t tell you that the event was actually an “Order Shipped.” This is where business events come in. Business events are high-quality, domain-specific data — they describe meaningful occurrences like “Payment Processed” or “Customer Registered.” Unlike raw data changes, these events provide the context and structure needed to power real-time analytics and unlock the full potential of AI and machine learning. These events, often called domain events, form the backbone of event-driven systems. Business/Domain Events in Practice For reliably generating, publishing and consuming these domain events, patterns like the transactional outbox, subscription, and event sourcing play crucial roles: Transactional outbox ensures that events are published consistently as part of the same database transaction that writes the underlying data, providing robustness even during failures. Subscription pattern enables systems to listen for and react to specific events in near real-time, enabling event-driven workflows and processes. Event sourcing goes further by making events the source of truth, storing all changes as an immutable sequence of events — empowering systems with a full audit history and the ability to reprocess or replay events at any time. By adopting event-driven architectures and producing event streams, organizations can move beyond traditional paradigms. This approach enables: Timely, actionable insights through real-time analytics. A foundation of rich, contextual data for AI and ML applications. Real-time notifications to trigger actions and inform stakeholders instantly. Better system design with domain-driven thinking at the core. Conclusion: Core domains in modern scalable operational systems should embrace business/domain events over Change Data Capture (CDC). Domain-driven design and event-driven architecture pave the way for creating future-proof systems. Scalable modeling as an event-centric approach provides a strong foundation for building long-lasting operational systems that deliver low latency and enable real-time analytics at any scale.
Many operational systems (e.g. SaaS platforms and transactional systems) are built around CRUD operations and batch processing, but these approaches often fall short when businesses demand real-time insights.
A common intermediate step is Change Data Capture (CDC), which reflects changes at the database level in near-real time. However, CDC primarily captures raw data changes (e.g., inserts, updates, deletes) and doesn’t provide the context of what those changes mean in the real world. For example, CDC might log an update to a database row, but it doesn’t tell you that the event was actually an “Order Shipped.”
This is where business events come in. Business events are high-quality, domain-specific data — they describe meaningful occurrences like “Payment Processed” or “Customer Registered.” Unlike raw data changes, these events provide the context and structure needed to power real-time analytics and unlock the full potential of AI and machine learning. These events, often called domain events, form the backbone of event-driven systems.
Business/Domain Events in Practice
For reliably generating, publishing and consuming these domain events, patterns like the transactional outbox, subscription, and event sourcing play crucial roles:
- Transactional outbox ensures that events are published consistently as part of the same database transaction that writes the underlying data, providing robustness even during failures.
- Subscription pattern enables systems to listen for and react to specific events in near real-time, enabling event-driven workflows and processes.
- Event sourcing goes further by making events the source of truth, storing all changes as an immutable sequence of events — empowering systems with a full audit history and the ability to reprocess or replay events at any time.
By adopting event-driven architectures and producing event streams, organizations can move beyond traditional paradigms. This approach enables:
- Timely, actionable insights through real-time analytics.
- A foundation of rich, contextual data for AI and ML applications.
- Real-time notifications to trigger actions and inform stakeholders instantly.
- Better system design with domain-driven thinking at the core.
Conclusion: Core domains in modern scalable operational systems should embrace business/domain events over Change Data Capture (CDC). Domain-driven design and event-driven architecture pave the way for creating future-proof systems.
Scalable modeling as an event-centric approach provides a strong foundation for building long-lasting operational systems that deliver low latency and enable real-time analytics at any scale.
