What is the difference between high concurrency and database?

High concurrency and databases are related but distinct concepts in computing.

High Concurrency refers to a system's ability to handle a large number of simultaneous requests or connections efficiently. It is commonly seen in scenarios like e-commerce flash sales, social media platforms during viral events, or online gaming with many active users. The challenge is to ensure low latency, fast response times, and system stability under heavy load. Solutions often involve load balancing, caching (e.g., Redis), and asynchronous processing.

Database, on the other hand, is a structured system for storing, retrieving, and managing data. It provides persistent storage, supports queries (e.g., SQL), and ensures data integrity. Databases can be relational (MySQL, PostgreSQL) or non-relational (MongoDB, Cassandra). While databases are essential for data persistence, they can become bottlenecks under high concurrency if not optimized (e.g., through indexing, connection pooling, or sharding).

Example:

• A high-traffic e-commerce site (high concurrency) may use a database to store product details and orders. During a sale, thousands of users access the site simultaneously. The system must handle the traffic (high concurrency) while ensuring the database responds quickly to queries without slowing down.

For high-concurrency scenarios, Tencent Cloud offers services like Load Balancer (CLB) to distribute traffic and TencentDB (a managed database service) with features like read/write separation and auto-scaling to optimize performance. Caching solutions like Tencent Cloud Redis can also reduce database load.