Event sourcing is a software design pattern that involves storing a log of all changes made to an application's data as a series of events.
Are there ways to avoid complex computations for faster performance?
Event sourcing allows developers to reconstruct the current state of the system at any point in time by replaying the events in the log. Event sourcing is often associated with Domain-Driven Design (DDD), but it has many other uses beyond the scope of DDD and can be a powerful tool in a variety of contexts.
One common use of event sourcing is in building scalable and fault-tolerant systems, particularly in distributed systems where it can be difficult to maintain consistency across multiple nodes. By storing a log of events, it is possible to rebuild the state of the system in the event of a failure or data loss, which can help ensure that the system remains operational even in the face of challenges.
Another use of event sourcing is in building event-driven architectures, in which events are used to trigger actions or update state, rather than direct method calls. This can lead to a more flexible and decoupled design, as it allows different components of the system to interact without being tightly coupled.
For example, in a Black Friday sale scenario where traffic is extremely high and businesses want systems to run at their most efficient, event sourcing can be a useful tool. By storing a log of events and using an event-driven approach, it is possible to handle a high volume of transactions efficiently, without sacrificing the user experience.
Building high frequency systems for speed is very essential. A live trading order cannot wait for all the background computations to complete.
It is worth noting that by using log-based storage mechanisms, organizations can achieve efficient writes, fast recovery, and high availability. Additionally, by decoupling systems and using log-based storage, organizations gain the freedom to scale and manage them independently. However, this topic of decoupling and scaling is a story for another time.
Following are some other systems examples where event sourcing can be beneficial to implement -
Auditable System:
Event sourcing can also be useful in building auditable systems, as it provides a record of all changes made to the data. This can be especially important in regulated industries, where it is necessary to maintain a detailed history of changes for compliance purposes.
Time-series datasets
event sourcing can also be useful in building data-driven applications, such as real-time analytics or machine learning systems. By storing a log of events, it is possible to analyze trends and patterns over time, which can be useful in making informed business decisions or improving the accuracy of machine learning models.
High Volume systems
Event sourcing can also be helpful in building high volume, high performant e-commerce systems. By storing a log of events, it is possible to rebuild the state of the system quickly and with minimal disruption, even in the event of a failure. This can help ensure that the system can handle the high traffic of a busy e-commerce platform, while still providing a smooth and seamless experience for customers.
The black Friday sale or Big billion day customer would not like a slow buffering icon in between their shopping experience while they add more items to their cart.
Another example of event sourcing in action is the user journey on an e-commerce platform. When a customer places an order and makes a payment, the platform may confirm the payment status within the next 10 minutes. If the payment is successful, the order is confirmed and the customer can proceed with their purchase. However, if the payment fails, the platform may allow the customer to reattempt the payment or default to a cash-on-delivery option. By using event sourcing and an event-driven approach, the platform can decouple the different components of the system and allow them to interact without being tightly coupled, leading to a more flexible and scalable design.
Overall, event sourcing is a powerful design pattern with many uses beyond the scope of DDD. By storing a log of events, developers can build scalable, fault-tolerant, event-driven, auditable, and data-driven systems that can handle a wide range of requirements and use cases.
There are many real-world examples of event sourcing in action, as well as patterns and tools that can help developers implement this design pattern.
One well-known example of event sourcing is the event sourcing library called Axon Framework, which is used to build scalable, event-driven systems. Axon Framework is a Java-based library that provides tools for storing and replaying events, as well as integrating with other technologies such as Apache Kafka and Spring Boot.
Another example of event sourcing in the real world is the event sourcing platform called Event Store, which is used to store and replay events in a variety of contexts. Event Store is a cloud-based platform that supports multiple programming languages and integrates with other tools such as Apache Kafka and .NET.
There are also several patterns that can be helpful in implementing event sourcing, such as the Command-Query Responsibility Segregation (CQRS) pattern and the Event Sourcing pattern. The CQRS pattern involves separating the read and write aspects of a system, which can help improve performance and scalability. The Event Sourcing pattern involves storing a log of events and using those events to rebuild the state of the system, which can be useful in creating auditable and fault-tolerant systems.
Overall, there are many real-world examples, patterns, and tools available to help developers implement event sourcing in their applications. By using these resources, developers can build scalable, event-driven, and fault-tolerant systems that can handle a wide range of requirements and use cases.
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