Mamba vs Spack

Mamba manages conda environments across Linux, macOS, Windows, API, and self-hosted setups. It creates and activates environments, installs packages, and runs commands inside them. It works with conda packages and supports most conda commands; its parallel downloads and libsolv solver speed package resolution. The framework includes the mamba command-line interface, the libmamba C++ library, micromamba, and Python bindings. Environment creation accepts text, Conda YAML, explicit, and conda-lock YAML specifications, and micromamba can install conda-lock files directly. The repoquery command searches repositories and can display direct, recursive, and reverse dependencies. Environments are self-contained prefixes that can manage native dependencies across programming languages. Mamba documents verification for package archives and extracted files, while repository index verification remains experimental. By default, it warns and asks for confirmation before transactions run package link scripts that can perform system operations. Mamba is free, open-source software under the BSD-3-Clause license, with lockfile support.

Spack is a package manager for installing scientific software on supercomputers, Linux, macOS, and Windows. It is designed for large supercomputing centers that share software across clusters and varied architectures, and is available at free. Users can choose package versions, compiler choices, target architectures, and compile-time options, while controlling direct and transitive dependencies. Spack can build stacks that combine Python or R packages with C, C++, or Fortran libraries. Each distinct package and dependency configuration receives its own prefix, so different builds can coexist without a new installation disrupting an existing one. Software can be installed to a user-selected directory without administrator privileges. Spack primarily builds customized software from source and also supports binary installation through build caches. It supports lockfiles, environment management, and private registries. Package recipes are Python scripts, and the `spack create` command generates starter boilerplate. The project is distributed under either the MIT license or Apache License 2.0, at the user's option.