AetherFS assists in the production, distribution, and replication of embedded databases and in-memory datasets. You can think of it like Docker, but for data.
AetherFS provides engineers with a platform to manage collections of files called datasets. It optimizes its use of the underlying blob store (AWS S3 or equivalent) to reduce cost to operators and improve performance for end users.
Why not use S3 directly or a file server?
While this is an option, there are several problems that arise with this solution. For example, to produce two references to the same dataset, you must upload the same set of files twice. If you want to produce three references, then three times (and so on). This comes at a cost of additional time in your pipeline and storage costs.
Instead, producers tag datasets in AetherFS. A tag can refer to a specific version (semantic or calendar) or a
channel that consumers can subscribe to (
stable, etc.). Instead of storing entire snapshots of datasets
in each version, AetherFS removes duplicated blocks between them. This allows clients to re-use blocks of data and only
download new or updated portions.
This project is under active development. The lists below detail aspirational features and documentation. For a completed list of features, see the roadmap below.
Since I’m mostly iterating on this project in my free time, I plan on using calendar versioning. Bugfixes and minor features can be introduced in any patch version but any major feature should wait for the next release. Releases happen in October, February, and June (every 4 months). Any security issues will be addressed in a timely manner, regardless of release schedule.
As the second major release of the AetherFS system, this will include additional security measures and helps simplify interaction for end users (provided there’s interest in the system).
This will be the initial release of AetherFS. It includes the “essentials”.