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mozilla
sccache
Rust2016–2026
mozilla / sccache

sccache

Sccache is a ccache-like tool. It is used as a compiler wrapper and avoids compilation when possible. Sccache has the capability to utilize caching in remote storage environments, including various cloud storage options, or alternatively, in local storage.

43Distinct people
50Mentions
1Explicit recommenders
7.9KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Sccache is a ccache-like tool. It is used as a compiler wrapper and avoids compilation when possible. Sccache has the capability to utilize caching in remote storage environments, including various cloud storage options, or alternatively, in local storage.

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

About long compile time, I recommend using sccache. It saved a lot of compile time for me. You can find how to install and use it here: https://github.com/mozilla/sccache

nicklauri used a recommendation phrase. One indexed comment matches. This is a phrase match, not a verdict.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year50 dated mentions

Observed mentions: 2016-11-22 14:31:46 UTC to 2026-10-01 16:47:51 UTC.

0369122016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20162017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 5 mentions; 1 submissions, 4 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 7 mentions; 1 submissions, 6 comments20212022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 7 mentions; 1 submissions, 6 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 11 mentions; 1 submissions, 10 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 5 mentions; 0 submissions, 5 comments2026-01-01 00:00:00 UTC to 2027-01-01 00:00:00 UTC (exclusive): 5 mentions; 2 submissions, 3 comments. Incomplete calendar period.2026*

* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC101
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC110
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC202
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC514
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC404
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC716
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC716
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC11110
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC202
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC505
2026 (partial)2026-01-01 00:00:00 UTC2027-01-01 00:00:00 UTC523

From the project README

An excerpt from the repository, fetched Nov 13, 2026.

Read the project’s introduction
sccache - Shared Compilation Cache sccache is a ccache-like compiler caching tool. It is used as a compiler wrapper and avoids compilation when possible, storing cached results either on local disk or in one of several cloud storage backends. Multi-level caching with automatic backfill is supported for hierarchical cache architectures (see Multi-Level Cache). sccache includes support for caching the compilation of Assembler, C/C++ code, Rust, as well as NVIDIA's CUDA using nvcc, and clang, AMD's ROCm HIP. sccache also provides icecream-style distributed compilation (automatic packaging of local toolchains) for all supported compilers (including Rust). The distributed compilation system includes several security features that icecream lacks such as authentication, transport layer encryption, and sandboxed compiler execution on build servers. See the distributed quickstart guide for more information. sccache is also available as a GitHub Actions to facilitate the deployment using GitHub Actions cache. Table of Contents (ToC) Installation Usage Build Requirements Build Separating caches between invocations Overwriting the cache Debugging Interaction with GNU make jobserver Known Caveats Storage Options Multi-Level (Hierarchical Caching) Local S3 R2 Redis Memcached Google Cloud Storage Azure GitHub Actions WebDAV (Ccache/Bazel/Gradle compatible) Alibaba OSS Tencent Cloud Object Storage Installation There are prebuilt x86-64 binaries available for Windows, Linux (a portable binary compiled against musl), and macOS on the releases page. Several package managers also include sccache packages, you can install the latest release from source using cargo, or build directly from a source checkout. macOS On macOS sccache can be installed via Homebrew: brew install sccache or via MacPorts: sudo port install sccache Windows On Windows, sccache can be installed via scoop: scoop install sccache or winget: winget install Mozilla.sccache Via cargo If you have a Rust toolchain installed you can install sccache using cargo. Note that this will compile sccache from source which is fairly resource-intensive. For CI purposes you should use prebuilt binary packages. cargo install sccache --locked Or, using cargo-binstall to install a prebuilt binary: cargo binstall sccache With Nix Sccache is available in nixpkgs, so if you don't need the latest version you can use that: buildInputs = [ pkgs.sccache ]; We also provide a flake with an overlay for getting the latest version: { inputs = { nixpkgs.url = "github:NixOS/nixpkgs/nixos-unstable"; sccache = { url = "github:mozilla/sccache"; inputs.nixpkgs.follows = "nixpkgs"; }; }; outputs = { self, nixpkgs, sccache, ... }: let system = "x86_64-linux"; pkgs = import nixpkgs { inherit system; overlays = [ sccache.overlays.default ]; }; in { devShells.${system}.default = pkgs.mkShell { buildInputs = [ pkgs.sccache ]; }; }; } Or use it directly from the flake without the overlay: nix run github:mozilla/sccache -- --help nix shell github:mozilla/sccache Usage Running sccache is like running ccache: prefix your compilation commands with it, like so: sccache gcc -o foo.o -c foo.c If you want to use sccache for caching Rust builds you can define build.rustc-wrapper in the cargo configuration file. For example, you can set it globally in $HOME/.cargo/config.toml by adding: [build] rustc-wrapper = "/path/to/sccache" Note that you need to use cargo 1.40 or newer for this to work. Alternatively you can use the environment variable RUSTC_WRAPPER: export RUSTC_WRAPPER=/path/to/sccache cargo build sccache supports gcc, clang, MSVC, rustc, NVCC, NVC++, hipcc, and Wind River's diab compiler. Both gcc and msvc support Response Files, read more about their implementation here. If you don't specify otherwise, sccache will use a local disk cache. sccache works using a client-server model, where the server runs locally on the same machine as the client. The client-server model allows the server to be more efficient by keeping some state in memory. The sccache command will spawn a server process if one is not already running, or you can run sccache --start-server to start the background server process without performing any compilation. By default sccache server will listen on 127.0.0.1:4226, you can specify environment variable SCCACHE_SERVER_PORT to use a different port or SCCACHE_SERVER_UDS to listen on unix domain socket. Abstract unix socket is also supported as long as the path is escaped following the format. For example: % env SCCACHE_SERVER_UDS=$HOME/sccache.sock sccache --start-server # unix socket % env SCCACHE_SERVER_UDS=\\x00sccache.sock sccache --start-server # abstract unix socket You can run sccache --stop-server to terminate the server. It will also terminate after (by default) 10 minutes of inactivity. Running sccache --show-stats will print a summary of cache statistics. Some notes about using sccache with Jenkins are here. To use sccache with cmake, provide the following command line arguments to cmake 3.4 or newer: -DCMAKE_C_COMPILER_LAUNCHER=sccache -DCMAKE_CXX_COMPILER_LAUNCHER=sccache The process for using sccache with MSVC and cmake, depends on which version of cmake you're using. For versions of cmake 3.24 and earlier, to generate PDB files for debugging with MSVC, you can use the /Z7 option. Alternatively, the /Zi option together with /Fd can work if /Fd names a different PDB file name for each object file created. Note that CMake sets /Zi by default, so if you use CMake, you can use /Z7 by adding code like this in your CMakeLists.txt: if(CMAKE_BUILD_TYPE STREQUAL "Debug") string(REPLACE "/Zi" "/Z7" CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG}") string(REPLACE "/Zi" "/Z7" CMAKE_C_FLAGS_DEBUG "${CMAKE_C_FLAGS_DEBUG}") elseif(CMAKE_BUILD_TYPE STREQUAL "Release") string(REPLACE "/Zi" "/Z7" CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE}") string(R
Read the full README on GitHub

What Hacker News says

50 sources
You should have set up https://github.com/mozilla/sccache at minimum. Setting up compiler caching is routine for people coming from older compiled language backgrounds but it's often missed by people coming from languages like JS/TS who have never been exposed to these ideas. There's a new project called kache https://github.com/kunobi-ninja/kache that takes this even further and handles more edge cases with worktrees, but it's newer. If you were pulling the entire project fresh and rebuilding everything in every worktree all the time without any caching then it would be frustrating. You could have asked your agent to set up basic caching and solved most of your problem in minutes.
In How to speed up the Rust compiler in September 2026
a_t48·Jul 15, 2026Submission

Show HN: An incremental build cache for Rust on GHA

Hi HN, I'm Kyle, the creator of Clipper, a container registry with 7x faster builds via lazy pulls and cache mount exports. In the process of implementing cache mount exports I ended up with a FUSE mounted filesystem backed by a remote content defined store. I went looking for fun things to do with it and found that there's not really a good way to keep Rust incremental build state around on ephemeral runners, so here we are. Rust generally uses https://github.com/mozilla/sccache for caching, but sccache disables itself when incremental compilation is enabled (https://github.com/mozilla/sccache/issues/236) and it isn't on Mozilla's roadmap to fix. It unfortunately doesn't really work on stable Rust (which uses mtime to decide when files have changed, rather than file contents), but maybe once https://github.com/rust-lang/cargo/issues/1413
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6 is stable it will be useful to someone.
5 points · Open discussion
> However, since worktrees are actually completely separate directories, you do have to install all your dependencies in each new worktree. What we need here is package caching in order to reduce download bandwidth and time, and its deduplication to avoid consuming storage space. This is important because worktrees are much more likely to share the same dependencies than unrelated projects. There may be language/toolchain specific solutions for this. In case of nodejs/frontend projects, both npm and pnpm implement download caching. However, npm seems to copy the relevant modules to the project directory, duplicating the files in storage. Pnpm[1] on the other hand, uses a global cache and symlinks/hardlinks the relevant version of the relevant module to the project tree. This will save a lot of space when multiple worktrees are used. In th
Read the rest
e python ecosystem, only conda[2] seems to provide this ability. The sccache project [3] provides similar advantages to C, C++, Rust and CUDA projects. It caches the binary artifacts of compilation, so that can be used to speed up even first compilation of projects. By default, these caches can be shared between different projects on the same system. But with networked storage backends, sccache can be used to share build artifacts across a network and even enable parallel builds on multiple builds. (Added: Cargo seems to globally cache sources and deal with it on its own without using any links at all.) Another important detail that might be worth consideration is the filesystem on which the worktrees reside. Copy-on-write filesystems like ZFS, btrfs and bcachefs provide automatic deduplication when copying files within a subvolume. I'm not sure what happens when worktrees are created by git. But they at least have tools to do manual deduplication (btrfs does). Perhaps we can just copy the package manager and build directories (like node_modules and build) from another worktree before running the development tools. Those tools are designed to handle stale cache anyway. So the wrong files wont be much of an issue for them. Perhaps tools like npm should look into making use of such filesystems, because you can get the same advantage as pnpm with practically no extra effort. [1] https://pnpm.io/motivation#saving-disk-space [2] https://docs.conda.io/projects/conda/en/latest/user-guide/co... [3] https://github.com/mozilla/sccache
In Why You Should Be Using Git Worktrees
Link times are the worst part but solveable with mold[1]/sold. Incremental compilations are usually an order of magnitude (or even two) faster than clean compiles but tbh that can still feel slow. Helped by using something like sccache[2] or even cranelift[3] when debugging. Still not as fast as having a hot-reloadable language but it gets you to a relatively pleasant speed still IME [1] https://github.com/rui314/mold [2] https://github.com/mozilla/sccache [3] https://github.com/rust-lang/rustc_codegen_cranelift
In Unexpected productivity boost of Rust
Compile times are still a bit much, but there are ways around it: - The insanely long times are only for the initial build. Further builds are incremental and more tolerable. - Compilation errors can be checked using 'cargo check'. It avoids the code generation step that's part of a build. I find myself doing it way more often than builds. So it's a time saver depending on how frequently you use it. - You can extend the incremental build mentioned above using sccache [1]. At the minimum, it allows you to share the build cache between all your local projects. So it saves time if your projects or other builds share a lot of common libraries (that's very common in Rust, though). But sccache can go further by using online build caches (for example, using S3) that can be shared between hosts. Finally, sccache also supports distributed builds i
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f you have a few machines sitting idle. (This is like distcc with extra features). [1]: https://github.com/mozilla/sccache
In Ruff: Python linter and code formatter written in Rust

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