Suppose you're developing a real-time trading platform where millions of transactions occur daily. How would you optimize transaction processing to ensure high throughput and minimal latency?
- Employ horizontal scaling by adding more servers to handle increased transaction volume
- Implement sharding to distribute data across multiple databases
- Use a message broker for asynchronous communication between trading components
- Utilize in-memory caching for frequently accessed data
In a real-time trading platform with a high transaction volume, optimizing transaction processing for high throughput and minimal latency is crucial. Implementing sharding to distribute data across multiple databases enables parallel processing of transactions, improving throughput. This approach allows each database shard to handle a subset of transactions, reducing contention and latency. Sharding also provides fault tolerance and scalability by distributing data and load across multiple servers.
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