When comparing Codefresh vs TFS, the Slant community recommends Codefresh for most people. In the question“What are the best continuous integration tools?” Codefresh is ranked 19th while TFS is ranked 26th. The most important reason people chose Codefresh is:
Once your images, or entire compositions, are ready to be deployed, Codefresh can do it automatically at the end of every build process. Alternatively, you can manually deploy with a single click.
Specs
Ranked in these QuestionsQuestion Ranking
Pros
Pro Easy deployment to any cloud
Once your images, or entire compositions, are ready to be deployed, Codefresh can do it automatically at the end of every build process. Alternatively, you can manually deploy with a single click.
Pro Early Feature Previews
You can share new feature implementations with your team by allowing them to instantly run your Docker image directly from Codefresh.
Pro Super fast builds
Caching build dependencies and docker layers speeds up the application builds.
Pro Concurrent
TFS contains very few locks and aims to be as suitable for multithreaded
systems as possible. It makes use of multiple truly concurrent structures
to manage the data, and scales linearly by the number of cores. This is
perhaps the most important feature of TFS.
Pro Usable in other systems
It was never planned to be Redox-only.
Pro Revision history
TFS stores a revision history of every file without imposing extra
overhead. This means that you can revert any file into an earlier version,
backing up the system automatically and without imposed overhead from
copying.
Pro Data integrity
TFS, like ZFS, stores full checksums of the file (not just metadata), and
on top of that, it is done in the parent block. That means that almost all
data corruption will be detected upon read.
Pro Copy-on-write semantics
Similarly to Btrfs and ZFS, TFS uses CoW semantics, meaning that no cluster
is ever overwritten directly, but instead it is copied and written to a new
cluster.
Pro O(1) recursive copies
Like some other file systems, TFS can do recursive copies in constant time,
but there is an unique addition: TFS doesn't copy even after it is mutated.
How? It maintains segments of the file individually, such that only the
updated segment needs copying.
Pro Guaranteed atomicity
The system will never enter an inconsistent state (unless there is hardware
failure), meaning that unexpected power-off won't ever damage the system.
Pro Improved caching
TFS puts a lot of effort into caching the disk to speed up disk accesses.
It uses machine learning to learn patterns and predict future uses to
reduce the number of cache misses. TFS also compresses the in-memory cache,
reducing the amount of memory needed.
Pro Better file monitoring
CoW is very suitable for high-performance, scalable file monitoring, but
unfortunately only few file systems incorporate that. TFS is one of those.
Pro All memory safe
TFS uses only components written in Rust. As such, memory unsafety is only
possible in code marked unsafe, which is checked extra carefully.
Pro Full coverage testing
TFS aims to be full coverage with respect to testing. This gives relatively
strong guarantees on correctness by instantly revealing large classes of
bugs.
Pro Improved garbage collection
TFS uses Bloom filters for space-efficient and fast garbage collection. TFS
allows the FS garbage collector to run in the background without blocking
the rest of the file system.
Pro SSD friendly
TFS tries to avoid the write limitation in SSD by repositioning dead sectors.
Pro Full-disk compression
TFS is the first file system to incorporate complete full-disk compression
through a scheme we call RACC (random-access cluster compression). This
means that every cluster is compressed only affecting performance slightly.
It is estimated that you get 60-120% more usable space.
Pro Asynchronous
TFS is asynchronous: operations can happen independently; writes and
reads from the disk need not block.
Cons
Con Not ready for use
While many components are complete, TFS itself is not ready for use.