Epoll vs. Io_uring in Linux: Which I/O Model Should You Choose?
When building high-performance applications on Linux, one of the most consequential architectural decisions you will make is how your program interacts with the operating system kernel to handle input and output. For years, epoll was the undisputed champion of scalable I/O multiplexing in Linux. Then, in 2019, the Linux kernel introduced io_uring, and the landscape shifted dramatically. Today, developers, systems engineers, and architects are actively debating which mechanism best serves modern workloads — and the answer is nuanced.
This article breaks down how each model works, where each excels, and when you should prefer one over the other.
Understanding Epoll: The Established Standard
Epoll is a Linux kernel system call designed for monitoring multiple file descriptors to see if I/O is possible on any of them. It was introduced in Linux 2.5.44 as a scalable improvement over the older select and poll syscalls, which suffered from O(n) time complexity as the number of monitored file descriptors grew.
With epoll, the kernel maintains an internal data structure that tracks which file descriptors you care about. When you call epoll_wait, the kernel returns only the descriptors that are ready for I/O, making the operation effectively O(1) with respect to the total number of watched descriptors. This made epoll the backbone of frameworks like Node.js, Nginx, Redis, and countless other high-throughput systems.
How Epoll Works in Practice
The epoll API consists of three core system calls: epoll_create, which creates an epoll instance; epoll_ctl, which adds, modifies, or removes file descriptors from the watch list; and epoll_wait, which blocks until one or more events are ready. Applications typically run an event loop that calls epoll_wait, processes the returned events, and loops again.
Epoll supports two triggering modes: level-triggered (the default, compatible with traditional POSIX semantics) and edge-triggered (which fires only when the state changes, offering higher performance but requiring more careful application logic). This flexibility is part of what made epoll so widely adopted.
Understanding Io_uring: The Modern Challenger
Io_uring, developed by Jens Axboe and merged into the Linux 5.1 kernel in 2019, takes a fundamentally different approach to asynchronous I/O. Rather than a notification model — where you learn a file descriptor is ready and then perform I/O — io_uring is a true asynchronous I/O submission and completion interface. You submit operations to a ring buffer shared between userspace and the kernel, and later collect results from a completion ring buffer.
The name comes directly from its core data structure: two ring buffers — a Submission Queue (SQ) and a Completion Queue (CQ) — that are memory-mapped into both userspace and kernelspace. This shared memory design means that, in many cases, submitting and completing I/O operations requires zero system calls at all.
What Makes Io_uring Fundamentally Different
The most significant architectural difference is that io_uring supports a genuinely asynchronous model for nearly all I/O types, including file I/O on local disks — something that epoll never natively supported. Epoll works exclusively with descriptors that support poll-like semantics, which excludes regular files. If you tried to use epoll with a regular file, it would always appear ready, making it useless for disk-bound workloads.
Io_uring, by contrast, can handle disk reads, disk writes, network sockets, pipes, timers, and even complex operations like accept, send, recv, splice, and fsync through the same unified interface. You can even chain operations using linked requests, so a read result can automatically feed into a subsequent write without returning to userspace.
Performance: Where Each Model Wins
For pure network I/O workloads with many concurrent connections — the classic C10K and C10M problem space — epoll is extremely well-optimized, battle-hardened, and has decades of production tuning behind it. The overhead per event is low, and the ecosystem of libraries and frameworks built around it is enormous.
However, io_uring begins to pull ahead in several measurable ways:
- Syscall batching: Io_uring can batch hundreds of I/O operations in a single
io_uring_entercall, or avoid syscalls entirely using the kernel polling mode (IORING_SETUP_SQPOLL), where a dedicated kernel thread continuously drains the submission queue. This dramatically reduces syscall overhead at high request rates. - Unified file and network I/O: Applications that mix disk and network operations — such as web servers serving static files — can handle both through a single io_uring instance rather than juggling multiple mechanisms.
- Fixed buffer and registered file descriptor support: Io_uring allows applications to pre-register buffers and file descriptors with the kernel, eliminating repeated validation costs on hot paths.
- Lower latency at scale: Benchmarks consistently show io_uring outperforming epoll-based approaches at high operation rates, particularly when using the zero-copy and kernel-polled modes.
Trade-offs and Maturity Considerations
Despite its performance advantages, io_uring comes with real trade-offs that any engineer must weigh carefully. Security concerns have been significant: io_uring has had a disproportionate number of kernel CVEs since its introduction, largely because its complexity and kernel-sharing model create a large attack surface. Some hardened Linux distributions and container environments (including certain Google and Android policies) have restricted or disabled io_uring by default.
Epoll, on the other hand, is simple, stable, and extremely well-understood. Its security track record is excellent, its documentation is comprehensive, and virtually every senior Linux engineer already knows how to use it correctly. For applications that are not pushing the absolute limits of I/O throughput, epoll remains an entirely rational choice.
When to Use Epoll vs. Io_uring
Choose epoll when you are building or maintaining network-heavy applications where stability, portability, and security are priorities. It is ideal for environments with strict kernel version requirements, since io_uring features improve significantly between kernel versions and older kernels may only support a subset of operations.
Choose io_uring when you are building new, performance-critical services on modern Linux kernels (5.10 LTS or newer is a reasonable minimum), especially when your workload involves mixed file and network I/O, high-frequency small operations, or when you need the absolute lowest latency at scale. Projects like Tokio (Rust's async runtime), liburing, and even modern versions of RocksDB are already leveraging io_uring to push performance boundaries.
The Bigger Picture
The debate between epoll and io_uring reflects a broader maturation in Linux I/O philosophy. Epoll solved the scalability problem of the late 1990s brilliantly. Io_uring is solving the syscall overhead and unified I/O problem of the 2020s. They are not directly competing for the same use case in every situation — rather, io_uring is expanding what is possible while epoll continues to serve the enormous installed base of production systems.
As kernel support matures and security issues are addressed through ongoing development, io_uring is likely to become the dominant I/O interface for high-performance Linux applications over the next several years. For now, understanding both models deeply gives you the architectural flexibility to make the right call for your specific workload, infrastructure, and risk tolerance.