Cachely vs Ccache

Cachely is a managed remote build cache for Nx, Lerna, Turborepo, Gradle, and Bazel. It shares build artifacts between CI runners and developer machines so supported tasks can reuse outputs. Cachely works through the listed remote-cache protocols and supports GitHub Actions, GitLab CI, CircleCI, Jenkins, Buildkite, Woodpecker, Drone, and self-hosted runners. Its dashboard reports cache hit rate, slow tasks, and estimated CI time and cost savings. Setup involves creating a workspace, generating a token, and configuring the build tool; the maker says this takes about five minutes. Tokens are hashed with SHA-256, scoped to one workspace, revocable, and fixed as read-only or read-write. Artifacts are immutable, content-addressed, served over HTTPS from Cloudflare R2, encrypted at rest, and removed after 20 days. Cachely has a free plan with 1 GiB storage and 500K monthly requests. Team costs $29.99 a month or $24.99 a month billed yearly. Enterprise pricing is custom.

Ccache is a build tool that can reduce repeated compilation work by storing prior results and recognizing when a single-file compilation recurs. It supports compilers such as GCC, Clang and MSVC, and languages including C, C++, assembler, CUDA, Objective-C and Objective-C++, with support varying by compiler and language. Runtime support includes Linux, macOS and native Windows at support level A, and Windows with MSYS2 and other Unix-like platforms at level B. Direct and depend modes can avoid running the preprocessor. Remote caching is possible through adaptable storage backends, with listed helpers for HTTP, HTTPS and Redis protocols. Ccache records cache hit and miss statistics, manages cache size, supports Zstandard compression, and uses BLAKE3 and XXH3 in its hashing and corruption checks. It works with Make, CMake, Ninja and Visual Studio. It is free software under the GNU GPL version 3 or later. Its scope has limits: multi-file compilation, linking and compilations with unsupported flags fall back to the real compiler. The project also cautions that cache misses add overhead and recommends measuring typical workloads.