Threads vs Processes

Both threads and processes are used to achieve concurrency and parallelism in software applications. While threads and processes share some similarities, there are also significant differences between them. Here are some of the main differences between threads and processes:


  1. A process is an instance of a program that is executed by the operating system.
  2. Each process runs in its own memory space and has its own set of system resources, such as file handles and network sockets.
  3. Processes are isolated from each other and communicate with each other using inter-process communication (IPC) mechanisms, such as pipes, sockets, or shared memory.
  4. Processes can be launched and managed by the operating system, and can run on separate CPUs or cores if available.
  5. Processes are heavy-weight compared to threads, and launching a new process incurs significant overhead in terms of memory allocation and process initialization.


  1. A thread is a separate path of execution within a process that can run concurrently with other threads in the same process.
  2. Threads share the same memory space as the process that they belong to, and can access the same set of system resources as other threads in the same process.
  3. Threads can communicate with each other using shared memory, and synchronization mechanisms such as locks and semaphores can be used to coordinate access to shared resources.
  4. Threads can be created and managed by the application itself, and are generally more lightweight and faster to create and destroy than processes.
  5. Multiple threads can run on a single CPU or core using time slicing, where each thread is given a small slice of time to run before switching to the next thread.


difference between thread vs process
In summary, processes provide a higher degree of isolation and security than threads, but are also more heavyweight and slower to create and manage. Threads, on the other hand, are more lightweight and can achieve higher levels of concurrency and parallelism within a single process, but must be carefully synchronized and coordinated to avoid race conditions and other issues. Which approach to use depends on the specific requirements of the application and the tradeoffs between performance, security, and isolation.