Event Streaming vs Event Sourcing: Core Concepts Quiz Quiz

Explore the essential differences and key concepts of event streaming and event sourcing with this quiz designed to evaluate your understanding of real-time data processing and state management approaches. Strengthen your grasp on event-driven architectures by distinguishing their fundamental principles and use cases.

1. Defining Event Streaming

   Which statement best describes event streaming in data systems?

   1. It is the process of creating a backup of relational databases.
   2. It is a way to store complete system state snapshots for future use.
   3. It is the continuous flow of events in real time to allow immediate processing.
   4. It is a method to rewrite historical events for different outcomes.

   Explanation: Event streaming enables systems to process data as it arrives, supporting scenarios like real-time analytics. Unlike storing snapshots, which focuses on system state rather than event flow, event streaming is about immediate event delivery. Backing up databases or rewriting history are different concepts and not tied to event streaming.

2. Purpose of Event Sourcing

   What is the main purpose of event sourcing in application architectures?

   1. Sending notifications to users instantly.
   2. Converting data formats between databases.
   3. Capturing all changes to application state as a sequence of events.
   4. Synchronizing files between devices.

   Explanation: Event sourcing involves recording every state-changing event, allowing reconstruction of state at any point. Sending notifications, file synchronization, or data conversion do not preserve a system’s change history as event sourcing does.

3. Difference in State Management

   In event sourcing, how is the current state of the system typically reconstructed?

   1. By creating new database tables each time.
   2. By analyzing log files for errors.
   3. By replaying all stored events in order.
   4. By merging multiple current snapshots.

   Explanation: Restoring the current system state in event sourcing is achieved by sequentially replaying all stored state-changing events. Merging snapshots or creating new tables are not standard practices for state recovery in event sourcing. Analyzing logs for errors is unrelated to state management.

4. Typical Use Case for Event Streaming

   Which scenario is best suited for event streaming solutions?

   1. Monitoring temperature data from thousands of sensors in real time.
   2. Generating monthly financial reports based on static data.
   3. Performing manual code reviews of application logic.
   4. Archiving old customer data for compliance.

   Explanation: Event streaming excels in situations where real-time data needs to be processed continuously, such as with sensor networks. Archiving, report generation, and code reviews do not leverage the real-time advantages of event streaming.

5. Event Sourcing and Auditability

   Why does event sourcing provide strong auditability for business applications?

   1. Because only the latest state is stored for efficiency.
   2. Because events are deleted after they are processed.
   3. Because all network traffic is archived.
   4. Because every state change is recorded as a discrete event.

   Explanation: Event sourcing logs every individual change, making it easy to audit and trace decisions and actions. Storing only the final state or deleting events eliminates change history, and archiving network traffic is unrelated to business events.

6. Immutability in Event-Based Systems

   How are events commonly treated in both event streaming and event sourcing paradigms?

   1. Events are grouped and overwritten daily.
   2. Events are immutable and cannot be changed once published.
   3. Events automatically self-delete after 24 hours.
   4. Events are edited frequently for data consistency.

   Explanation: Immutability ensures that events remain unchanged, preserving a reliable history. Editing, overwriting, or auto-deleting events would undermine the reliability and traceability needed in event-driven systems.

7. Event Storage Comparison

   What distinguishes event storage in event sourcing compared to event streaming?

   1. Event streaming always encrypts events while event sourcing does not.
   2. Event streaming cannot handle more than ten events at a time.
   3. Event sourcing deletes all previous events after state is calculated.
   4. Event sourcing stores all events permanently to represent system state, while event streaming may retain events only temporarily for processing.

   Explanation: Event sourcing relies on permanent event storage for state reconstruction, whereas event streaming often focuses on processing and may not require long-term retention. Encryption and event volume limits are not defining differences, and event sourcing does not routinely delete historical events.

8. Handling of Late Events

   When a late event (out-of-order event) arrives in an event streaming system, how is it typically handled?

   1. The system can reorder or compensate for the late event during processing.
   2. Late events cause the system to shut down.
   3. The late event overwrites all previous events.
   4. The system always ignores late events.

   Explanation: Event streaming systems often include logic to handle and process late or out-of-order events. Ignoring, overwriting, or shutting down due to late events would result in data loss or unnecessary failures and are not standard behaviors.

9. Historical Data Replay

   Which feature does event sourcing enable that event streaming alone does not guarantee?

   1. Processing events at the highest possible speed.
   2. Replaying the complete history of system changes to recreate any past state.
   3. Storing duplicate events for redundancy.
   4. Automatically correcting all inaccurate events.

   Explanation: A core value of event sourcing is that the entire event log allows reconstruction of any previous state. High speed processing, redundancy, or automatic corrections are not unique to event sourcing, and replaying system history is not always feasible with event streaming alone.

10. Real-Time Processing Focus

    Which method is typically more focused on delivering low-latency, real-time updates to consumers?

    1. Event streaming.
    2. Event storing.
    3. Event sorting.
    4. Event browsing.

    Explanation: Event streaming is optimized for immediate delivery and processing of events, supporting applications that require up-to-date information. Event storing, sorting, or browsing do not prioritize or inherently deliver real-time updates to users.