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Design a scalable and fault-tolerant real-time trading system where every transaction is executed only once. Give a detailed explanation of your design and the technologies you would use.

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Designing a Scalable and Fault-tolerant Real-time Trading System

Designing a real-time trading system requires a deep understanding of the various components and factors that impact the performance and reliability of the system. The key factors that need to be considered while designing such a system are scalability, fault-tolerance, and idempotency.

Scalability

The scalability of the system refers to its ability to handle an increasing number of transactions. To achieve scalability, we would need to design the system with a distributed architecture. The system can be divided into multiple components, such as order management, trade execution, and risk management, and each of these components can be distributed across multiple nodes. This would enable the system to handle an increasing number of transactions, as the load can be distributed across multiple nodes. One of the technologies that we can use to achieve scalability is Apache Kafka, which is a distributed streaming platform that can handle high throughput and ensure low latency.

Fault-Tolerance

Fault-tolerance is the ability of the system to continue functioning even in the event of a failure. To achieve fault-tolerance, we would need to design the system with redundancy in mind. This would mean that if a node fails, the system can still continue processing transactions without any disruption. One of the technologies that we can use to achieve fault-tolerance is Apache ZooKeeper, which is a distributed coordination service that can ensure that the system can continue functioning even in the event of a failure.

Idempotency

Idempotency is the ability of the system to ensure that every transaction is executed only once. To achieve idempotency, we would need to design the system with a unique identifier for each transaction. This unique identifier can be generated by the system when a transaction is initiated, and it can be used to ensure that the transaction is not executed multiple times. One of the technologies that we can use to achieve idempotency is Apache Cassandra, which is a distributed NoSQL database that can handle high write throughput and ensure that every transaction is executed only once.

Summary

In summary, designing a real-time trading system requires a deep understanding of the various factors that impact the performance and reliability of the system. To achieve scalability, fault-tolerance, and idempotency, we can use technologies such as Apache Kafka, Apache ZooKeeper, and Apache Cassandra.

References

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