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If you keep all order book changes for a large number of financial instruments volume adds up quickly.

Me too. Is is really hard for me to understand, what XTX is actually doing. Trading? VC? AI/ML?

Have you seen their portfolio?

PS: Company seems legit. Impressive growth. But I still don't understand what they are doing. Provide "electronic liquidity". Well....

If price action trading is horoscopes for adults, they're a modern a day oracle.

In theory what they are doing of value, is that at any time you can go to an exchange and say "I want to buy x" or "I want to sell y" and someone will buy it from you our sell it from you... at a price that's likely to be the accurate price.

At the extreme if nobody was providing this service, investors (e.g. pension funds), wouldn't be confident that they can buy/sell their assets as needed in size and at the right price... and because of that, in aggregate stocks would be worth less, and companies wouldn't be able to raise as much capital.

The theoretical model is: - You want to have efficient primary markets that allow companies to raise a lot of assets at the best possible prices - To enable efficient primary markets, investors want efficient secondary markets (so they don't need to buy and hold forever, but feel they can sell) - To enable efficient secondary markets, you need many folks that are in the business of XTX ... it just so happens that XTX is quite good at it, and so they do a lot of this work.

Yes, that would be very useful, we just didn't get to it and we didn't want perfect to be the enemy of good, since otherwise we would have never open sourced :).

But if we have the time it would definitely be a good addition to the docs.

I have worked on exabyte-scale storage engines. There is a good engineering reason for this type of limitation.

If you had 1 KiB average file size then you have quadrillions of metadata objects to quickly search and manage with fine-granularity. The kinds of operations and coordination you need to do with metadata is difficult to achieve reliably when the metadata structure itself is many PB in size. There are interesting edge cases that show up when you have to do deep paging of this metadata off of storage. Making this not slow requires unorthodox and unusual design choices that introduce a lot of complexity. Almost none of the metadata fits in memory, including many parts of conventional architectures we assume will always fit in memory.

A mere trillion objects is right around the limit of where the allocators, metadata, etc can be made to scale with heroic efforts before conventional architectures break down and things start to become deeply weird on the software design side. Storage engines need to be reliable, so avoiding that design frontier makes a lot of sense if you can avoid it.

It is possible to break this barrier but it introduces myriad interesting design and computer science problems for which there is little literature.

Yeah, that was the first thing I checked as well. Being suited for small / tiny files is a great property of the SeaweedFS system.

Shameless plug: https://github.com/Barre/ZeroFS

I initially developed it for a usecase where I needed to store billions of tiny files, and it just requires a single s3 bucket as infrastructure.

What happens if you put a tiny file on it then? Bad perf, possible file corruption, ... ?

Trading using ML.

(Disclaimer: I'm one of the authors of TernFS and while we evaluated Ceph I am not intimately familiar with it)

Main factors:

* Ceph stores both metadata and file contents using the same object store (RADOS). TernFS uses a specialized database for metadata which takes advantage of various properties of our datasets (immutable files, few moves between directories, etc.).

* While Ceph is capable of storing PBs, we currently store ~600PBs on a single TernFS deployment. Last time we checked this would be an order of magnitude more than even very large Ceph deployments.

* More generally, we wanted a system that we knew we could easily adapt to our needs and more importantly quickly fix when something went wrong, and we estimated that building out something new rather than adapting Ceph (or some other open source solution) would be less costly overall.

CephFS implements a (fully?) POSIX filesystem while it seems that TernFS makes tradeoffs by losing permissions and mutability for further scale.

Their docs mention they have a custom kernel module, which I suppose is (today) shipped out of tree. Ceph is in-tree and also has a FUSE implementation.

The docs mention that TernFS also has its own S3 gateway, while RADOSGW is fully separate from CephFS.

The seamless realtime intercontinental replication is a key feature for us, maybe the most important single feature, and AFAIK you can’t do that with Ceph (even if Ceph could scale to our original 10 exabyte target in one instance).

Licensing

TernFS is Free Software. The default license for TernFS is GPL-2.0-or-later.

The protocol definitions (go/msgs/), protocol generator (go/bincodegen/) and client library (go/client/, go/core/) are licensed under Apache-2.0 with the LLVM-exception. This license combination is both permissive (similar to MIT or BSD licenses) as well as compatible with all GPL licenses. We have done this to allow people to build their own proprietary client libraries while ensuring we can also freely incorporate them into the GPL v2 licensed Linux kernel.

could be a tectonic shift in the open source filesystem landscape?

I see what you did there.

And yet no one needed a blockchain to implement this.