A founder's guide to Linux I/O: Epoll vs. io_uring for performance

A technical breakdown of Linux's two primary high-performance I/O interfaces. We analyze their architectural differences and performance claims to guide decisions for latency-sensitive applications and services.

The Answer Up Front

For new, high-performance network services like proxies, databases, or message queues, building on io_uring is the correct long-term choice. It offers a fundamentally more efficient I/O model by minimizing kernel transitions. Teams with existing, stable applications built on epoll should skip a rewrite unless they are severely bottlenecked by syscall overhead. The migration cost is high. The bottom line is that io_uring represents the future of performant I/O on Linux, but its complexity makes epoll a pragmatic, well-supported option for many less demanding workloads.

Methodology

This v0 review analyzes the technical comparison and performance claims presented in a blog post by Sibexico, published at sibexi.co/posts/epoll-vs-io_uring/. The analysis was conducted on June 21, 2026. Our review covers the architectural explanations of epoll (readiness-based I/O) and io_uring (completion-based I/O), the provided code patterns, and the author's performance assertions. This review does not include our own independent benchmarks, analysis of long-term production stability, or a comparative review of high-level libraries that abstract these kernel interfaces. This piece is based entirely on the claims and data in the source article. Independent benchmarks are pending for a v1 update.

What It Does

epoll and io_uring are Linux kernel mechanisms for handling many I/O operations efficiently. They solve the same problem with fundamentally different approaches.

epoll: The readiness model

Introduced in Linux 2.5.44, epoll allows a program to monitor many file descriptors to see if I/O is possible on any of them. The workflow involves two main steps. First, you register file descriptors (like network sockets) with an epoll instance. Second, you call epoll_wait(), a single system call that blocks until one or more of those descriptors are "ready" for I/O (e.g., data has arrived to be read). Your application then performs the actual read() or write() operation, which is a separate syscall. It's an efficient notification system, vastly superior to older select() and poll() calls, but it still requires at least two syscalls per operation: one to wait, one to act.

io_uring: The completion model

io_uring, available since Linux 5.1, is a more recent and powerful interface. It operates on a completion model using two ring buffers, the Submission Queue (SQ) and Completion Queue (CQ), which are shared between your application and the kernel. Instead of asking if a socket is ready, you submit a request for an entire operation (e.g., "read 1024 bytes from this socket into this buffer") to the SQ. You can submit many such requests at once. The kernel processes these requests asynchronously in the background and places a completion event on the CQ when an operation finishes. This design can reduce I/O to zero syscalls in some modes, as both submission and completion can be managed by manipulating the shared memory rings.

More than just network I/O

A critical distinction is that io_uring is a general-purpose asynchronous interface. The author notes it can handle network sockets, file I/O (both buffered and direct), timers, and other operations through a unified API. epoll is limited to readiness notifications on file descriptors, which typically means network I/O.

What's Interesting / What's Not

The most interesting aspect is the dramatic reduction in kernel-userspace transitions. The source article claims io_uring can achieve significantly higher throughput and lower latency precisely because it avoids the syscall-per-operation overhead inherent in the epoll model. By submitting batches of I/O requests and reaping their results later, an application can keep the CPU busy with other work instead of waiting on the kernel. This is particularly impactful for applications like databases or load balancers that handle immense I/O volume.

The primary drawback is complexity. Programming directly against the io_uring interface is substantially more difficult than using epoll. It requires careful management of the shared ring buffers, memory barriers, and the lifecycle of I/O operations. This complexity is why most developers will use a library like liburing in C/C++ or a runtime that integrates io_uring support, like Tokio for Rust. The performance benefits are not free; they come at the cost of a steeper learning curve and more complex code.

For many standard web services that are not operating at the performance edge, the benefits of io_uring may not outweigh this complexity. If your application's bottleneck is business logic, database queries, or external API calls, optimizing the I/O model from epoll to io_uring will yield little improvement.

Pricing

Not applicable. epoll and io_uring are Linux kernel features available since kernel versions 2.5.44 and 5.1, respectively. They are free to use. (Pricing snapshot: June 21, 2026).

Verdict

For greenfield projects where performance is a core product requirement, choosing a modern framework built on io_uring is the superior technical decision. The architectural benefits of a true asynchronous, completion-based model provide a higher performance ceiling and greater efficiency, especially for I/O-bound workloads. However, epoll remains a perfectly valid, battle-tested, and simpler choice. For existing systems or for applications where developer velocity and a mature ecosystem are prioritized over absolute peak I/O throughput, sticking with epoll is a pragmatic and low-risk engineering decision. The choice depends directly on whether your application's primary bottleneck is, or will be, syscall overhead.

What We'd Test Next

Our v1 update would focus on independent benchmarks. First, we would test a high-connection, small-payload echo server to measure requests per second and CPU utilization under load, directly comparing epoll and io_uring implementations. Second, we would benchmark a file-serving application, comparing io_uring's native asynchronous file I/O against a traditional epoll-with-a-thread-pool architecture. Finally, we would evaluate the performance overhead and developer ergonomics of popular abstraction libraries like liburing to quantify the trade-offs versus programming the raw kernel interface.

The investor read

The adoption of io_uring is a key technical signal for identifying next-generation infrastructure software. Companies building databases (ScyllaDB), streaming platforms (Redpanda), and other high-performance systems often build their competitive moat on top of io_uring's efficiency. When evaluating a company whose value proposition is superior performance on commodity hardware, check their technical stack. A deep investment in io_uring indicates a sophisticated systems engineering team and a potentially durable technical advantage over incumbents built on older epoll or thread-per-connection architectures. It's a proxy for a team that understands and can execute on low-level optimization, which is critical for infrastructure tooling.

Pull quote: “The performance benefits are not free; they come at the cost of a steeper learning curve and more complex code.”