AppVeyor vs TFS

AppVeyor is free for public GitHub repositories.

AppVeyor has a build environment for Windows available.

Well I suggest you check it out for yourself, but what I like most is that it's simple yet effective: no bells and whistles, simple black/grey/light-blue/white color scheme, it's immediately clear where you have to go for each specific task, and build settings pages are like that as well. Getting a 'standard' build running literally took me a minute the first time I used it.

AppVeyor allows the user to login to the actual build VM.

There's practically no setup involved prior to working with AppVeyor: simply sign in, add the project, and start a new build.

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.

It was never planned to be Redox-only.

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.

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.

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.

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.

The system will never enter an inconsistent state (unless there is hardware
failure), meaning that unexpected power-off won't ever damage the system.

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.

CoW is very suitable for high-performance, scalable file monitoring, but
unfortunately only few file systems incorporate that. TFS is one of those.

TFS uses only components written in Rust. As such, memory unsafety is only
possible in code marked unsafe, which is checked extra carefully.

TFS aims to be full coverage with respect to testing. This gives relatively
strong guarantees on correctness by instantly revealing large classes of
bugs.

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.

TFS tries to avoid the write limitation in SSD by repositioning dead sectors.

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.

TFS is asynchronous: operations can happen independently; writes and
reads from the disk need not block.