Hacker News Reader

Comment by zasdffaa | Hacker News Reader

> Their vision was to build the hardest parts of building a database, such as transactions, fault-tolerance, high-availability, elastic scaling, etc. This would free users to build higher-level (Layers) APIs [1] / libraries [2] on top.

That is very interesting and simple and valuable insight that seems to be missing from the wiki page. But also from the wiki page <https://en.wikipedia.org/wiki/FoundationDB>, this:

The design of FoundationDB results in several limitations:

Long transactions- FoundationDB does not support transactions running over five seconds.

Large transactions - Transaction size cannot exceed 10 MB of total written keys and values.

Large keys and values - Keys cannot exceed 10 kB in size. Values cannot exceed 100 kB in size.

Those (unless worked around) would be absolute blockers to several systems I've worked on.

View on HN

This project (mvSQLite) appears to have found a way around the 5s transaction limit as well as the size, so that's really promising. That being said, I believe the new RedWood storage engine in FDB 7.0+ is making inroads in eliminating some of these limitations, and this project should also benefit from that new storage engine...(prefix compression is a big one).

A simple workaround is to store “bulk data” in an external system like blob storage and reference that from the DB.

but now transactional guarantees only extend to the id stored in the DB, and not on the external storage.

Therefore, it's possible that the id is invalid (for the external storage) when referenced in the future. I think doing so only adds complexity as system grows.

It would be better to chunk your blob data to fit the DB, imho. It beats introducing external blob storage in the long run.

> but now transactional guarantees only extend to the id stored in the DB, and not on the external storage.

Depends! If the ID is a cryptographic hash, then as long as the blob is uploaded first, then the DB can't be inconsistent with the blob[1].

A Merkle Tree also allows "updates" by chunking the data into some convenient size, say 64 MB, and then building a new tree for each update and sticking that into the database.

[1] With the usual caveats that nobody is manually mucking about with the blob store, that it hasn't "lost" any blobs due to corruption, etc, etc...

But if you upload to the blob store first, then add to the transaction (in your db insert) with the id (hash or not), what happens if the db transaction fails? You now have to work out a way to delete off the blob external store. Or change your application so that that it doesn't matter if it's left on the blob store ('cept for money).

> With the usual caveats that nobody is manually mucking about with the blob store, that it hasn't "lost" any blobs due to corruption, etc, etc...

Yeah, with those caveats. But how do you make sure they apply? If someone does manually muck about with the blob store, or it does lose blobs due to corruption, then your transaction is retroactively "un-atomicized" with no trace thereof in the actual DB.

If corruption happens then any guarantees by the hardware are voided, and the software guarantees (of durability) which are built o the hardware guarantees are equally voided. So corruption -> dead in the water.

But otherwise I agree.

Reply on news.ycombinator.com