What strategies would you employ to ensure data consistency in a distributed system?

During my final year in college, I worked on a group project to create a data management system for a local library. We had to ensure that multiple users could borrow and return books simultaneously without causing data inconsistencies. To tackle this, we implemented a basic version of a distributed database where we used locks to manage access to shared resources. I learned how important it was to manage user access effectively, and we also discussed strategies like using timestamps to resolve conflicts. This experience taught me the significance of data consistency in a real-world application, even in a simplified environment.

In my internship at an event management company, I was involved in developing a registration system for multiple events. We faced challenges with users registering for the same event simultaneously, which could lead to overbooking. My team decided to use a queue system that temporarily held registration requests. This ensured that requests were processed one at a time. Additionally, we implemented a notification system that updated users about their registration status. This experience highlighted the importance of maintaining data consistency and how effective strategies can enhance user experience.

In my first job at a startup focused on e-commerce, we had to ensure data consistency across our product inventory system. We faced instances where multiple users attempted to purchase the last item in stock. To solve this, we adopted a solution involving optimistic concurrency control, where we allowed users to proceed with the checkout process but verified the stock levels right before finalizing the purchase. This approach helped reduce conflicts and maintain a consistent view of available inventory, which was crucial for customer satisfaction and trust.