Concurrency is the ability of a system to execute multiple tasks at the same time, improving efficiency.
Concurrency is when a system handles multiple tasks at the same time by switching between them rapidly. Tasks progress simultaneously, even if they do not execute at the exact same moment.
Think of a chef cooking multiple dishes. They do not cook one dish start-to-finish, then start the next. They chop vegetables for dish A, then while those cook, prep dish B, then check on dish A. Multiple dishes progress at once.
Concurrency: Managing multiple tasks, switching between them. One cook, multiple dishes.
Parallelism: Executing multiple tasks simultaneously. Multiple cooks, each cooking a dish at the same time.
Your phone handles concurrency - music plays while you browse, notifications arrive while you type. It switches between tasks so fast it feels simultaneous.
Without Concurrency: Your app freezes while waiting for an API response. Users cannot click anything. Terrible experience.
With Concurrency: API request happens in the background. Users keep interacting. App stays responsive.
Modern applications must handle many things at once - user input, network requests, animations, background tasks. Concurrency makes this possible.
JavaScript Example (async/await):
() {
user = ();
posts = ();
}
() {
[user, posts] = .([
(),
()
]);
}
Meet the strictest isolation level that treats your database like there's only one user at a time, ensuring perfect consistency at the cost of performance.
Database Isolation Levels The second approach is concurrent - both requests happen simultaneously.
Web Servers: Handle thousands of requests concurrently. While one request waits for database, the server processes other requests.
Video Streaming: Netflix downloads the next video chunk while you watch the current one. Smooth experience with no buffering.
Databases: Process multiple queries concurrently. While one query reads from disk, others execute.
Race Conditions: Two tasks modify the same data simultaneously. Results become unpredictable.
Deadlocks: Two tasks wait for each other to release resources. Neither can proceed. System freezes.
Synchronization: Coordinating tasks so they do not interfere with each other requires careful programming.
These bugs are notoriously difficult to debug because they are often unpredictable and hard to reproduce.
Async/Await: JavaScript, Python, C# - makes concurrent code readable.
Threads: Java, C++ - execute tasks in parallel (if multiple CPU cores available).
Event Loops: Node.js uses this to handle thousands of concurrent connections efficiently.
Message Queues: Decouple tasks. Producer adds tasks, consumers process them concurrently.
Anytime your app waits for something - network requests, file I/O, database queries. Instead of blocking, handle other work concurrently.
Do not use concurrency for CPU-intensive calculations that do not wait. That needs parallelism (multiple cores) instead.
Concurrency is fundamental to building responsive, efficient applications. Understanding it transforms how you write code - from blocking, slow programs to responsive, efficient ones.
Start simple with async/await patterns. As you grow, explore more advanced concurrency tools and patterns. The learning curve is worth it.
