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+title = "Related work"
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+
+## Context
+
+Data storage is critical: it can lead to data loss if done badly and/or on hardware failure.
+Filesystems + RAID can help on a single machine but a machine failure can put the whole storage offline.
+Moreover, it put a hard limit on scalability. Often this limit can be pushed back far away by buying expensive machines.
+But here we consider non specialized off the shelf machines that can be as low powered and subject to failures as a raspberry pi.
+
+Distributed storage may help to solve both availability and scalability problems on these machines.
+Many solutions were proposed, they can be categorized as block storage, file storage and object storage depending on the abstraction they provide.
+
+## Overview
+
+Block storage is the most low level one, it's like exposing your raw hard drive over the network.
+It requires very low latencies and stable network, that are often dedicated.
+However it provides disk devices that can be manipulated by the operating system with the less constraints: it can be partitioned with any filesystem, meaning that it supports even the most exotic features.
+We can cite [iSCSI](https://en.wikipedia.org/wiki/ISCSI) or [Fibre Channel](https://en.wikipedia.org/wiki/Fibre_Channel).
+Openstack Cinder proxy previous solution to provide an uniform API.
+
+File storage provides a higher abstraction, they are one filesystem among others, which means they don't necessarily have all the exotic features of every filesystem.
+Often, they relax some POSIX constraints while many applications will still be compatible without any modification.
+As an example, we are able to run MariaDB (very slowly) over GlusterFS...
+We can also mention CephFS (read [RADOS](https://ceph.com/wp-content/uploads/2016/08/weil-rados-pdsw07.pdf) whitepaper), Lustre, LizardFS, MooseFS, etc.
+OpenStack Manila proxy previous solutions to provide an uniform API.
+
+Finally object storages provide the highest level abstraction.
+They are the testimony that the POSIX filesystem API is not adapted to distributed filesystems.
+Especially, the strong concistency has been dropped in favor of eventual consistency which is way more convenient and powerful in presence of high latencies and unreliability.
+We often read about S3 that pioneered the concept that it's a filesystem for the WAN.
+Applications must be adapted to work for the desired object storage service.
+Today, the S3 HTTP REST API acts as a standard in the industry.
+However, Amazon S3 source code is not open but alternatives were proposed.
+We identified Minio, Pithos, Swift and Ceph.
+Minio/Ceph enforces a total order, so properties similar to a (relaxed) filesystem.
+Swift and Pithos are probably the most similar to AWS S3 with their consistent hashing ring.
+However Pithos is not maintained anymore. More precisely the company that published Pithos version 1 has developped a second version 2 but has not open sourced it.
+Some tests conducted by the [ACIDES project](https://acides.org/) have shown that Openstack Swift consumes way more resources (CPU+RAM) that we can afford. Furthermore, people developing Swift have not designed their software for geo-distribution.
+
+There were many attempts in research too. I am only thinking to [LBFS](https://pdos.csail.mit.edu/papers/lbfs:sosp01/lbfs.pdf) that was used as a basis for Seafile. But none of them have been effectively implemented yet.
+
+## Existing software
+
+**[MinIO](https://min.io/):** MinIO shares our *Self-contained & lightweight* goal but selected two of our non-goals: *Storage optimizations* through erasure coding and *POSIX/Filesystem compatibility* through strong consistency.
+However, by pursuing these two non-goals, MinIO do not reach our desirable properties.
+Firstly, it fails on the *Simple* property: due to the erasure coding, MinIO has severe limitations on how drives can be added or deleted from a cluster.
+Secondly, it fails on the *Internet enabled* property: due to its strong consistency, MinIO is latency sensitive.
+Furthermore, MinIO has no knowledge of "sites" and thus can not distribute data to minimize the failure of a given site.
+
+**[Openstack Swift](https://docs.openstack.org/swift/latest/):**
+OpenStack Swift at least fails on the *Self-contained & lightweight* goal.
+Starting it requires around 8GB of RAM, which is too much especially in an hyperconverged infrastructure.
+We also do not classify Swift as *Simple*.
+
+**[Ceph](https://ceph.io/ceph-storage/object-storage/):**
+This review holds for the whole Ceph stack, including the RADOS paper, Ceph Object Storage module, the RADOS Gateway, etc.
+At its core, Ceph has been designed to provide *POSIX/Filesystem compatibility* which requires strong consistency, which in turn
+makes Ceph latency-sensitive and fails our *Internet enabled* goal.
+Due to its industry oriented design, Ceph is also far from being *Simple* to operate and from being *Self-contained & lightweight* which makes it hard to integrate it in an hyperconverged infrastructure.
+In a certain way, Ceph and MinIO are closer together than they are from Garage or OpenStack Swift.
+
+**[Pithos](https://github.com/exoscale/pithos):**
+Pithos has been abandonned and should probably not used yet, in the following we explain why we did not pick their design.
+Pithos was relying as a S3 proxy in front of Cassandra (and was working with Scylla DB too).
+From its designers' mouth, storing data in Cassandra has shown its limitations justifying the project abandonment.
+They built a closed-source version 2 that does not store blobs in the database (only metadata) but did not communicate further on it.
+We considered there v2's design but concluded that it does not fit both our *Self-contained & lightweight* and *Simple* properties. It makes the development, the deployment and the operations more complicated while reducing the flexibility.
+
+**[Riak CS](https://docs.riak.com/riak/cs/2.1.1/index.html):**
+*Not written yet*
+
+**[IPFS](https://ipfs.io/):**
+*Not written yet*
+
+## Specific research papers
+
+*Not yet written*