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Comment by biokoda | Hacker News Reader

SQLite's concurrency support is irrelevant. ActorDB is a sharded by default type of database. The point of ActorDB is to split your dataset into "actors". Actor is an individual unit of storage (a sqlite database). As such your entire database is scalable across any number of nodes.

A natural fit is something like dropbox, evernote, feedly, etc. Every user has his own actor and it is a full SQL database. Which makes the kind of queries dropbox would need very easy to do.

It also has a KV store option. This is basically a large table across all your servers. This table can have foreign key sub tables. From my understanding of FoundationDB this part is closer to what they were offering.

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It's not irrelevant. It means your ability to perform concurrent transactions depends entirely upon your ability to decompose your data into a very large number of different actors, otherwise you're bound to be hampered by SQLite's global lock. If you decompose too far you'll end up doing cross-actor transactions, which per the documentation has a substantial performance impact.

This is not to rubbish it - I've not used it after all - but the claims being made for ActorDB are pretty far away from the claims made for Foundation.

All distributed databases shard data. If you hammer at only a specific shard area, performance will be limited to the speed of that shard.

ActorDB fits a specific data model extremely well. Some less so. But that is the case with all databases.

> All distributed databases shard data. If you hammer at only a specific shard area, performance will be limited to the speed of that shard.

Agreed. And what I'm saying is that it appears that ActorDB's per-shard area concurrency is limited to one writer. And that means that SQLite's concurrency support is (contrary to your earlier post) extremely relevant: not just in terms of pure performance, but also ability to perform concurrent operations. If you need more concurrency, your only choice is to shard extremely heavily (which might mean you require more cross-shard operations, which are apparently slow).

As you say, some data models fit the actor model well, but this is still a far cry from the capabilities that were promised by FoundationDB.

FoundationDB was single process. They had no per-node writer concurrency.

The reason why I said sqlite concurrency support is irrelevant is because ActorDB serializes requests anyway. It must do so for safe replication.

> FoundationDB was single process. They had no per-node writer concurrency.

Interesting - I didn't know that. Even so, it depends on what kind of writer concurrency we're talking about, I guess - I presume that ActorDB is limited not just by having to run requests one at a time per-process (which is a legitimate tactic to avoid latching overheads and so on), but by also not being able to run any new transactions against an actor that's received a write until that write commits?

> The reason why I said sqlite concurrency support is irrelevant is because ActorDB serializes requests anyway. It must do so for safe replication.

Do you mean by this that the entire cluster can only perform one request at a time? Or am I misreading you?

Individual actors are individual units of replication. What one actor is writing is concurrent to what another is doing.

Read/write calls to an actor are sequential. I'm quite sure this is how other KV stores like Riak do as well. They have X units per server and those process requests sequentially. Their actual concurrency is basically how many units per server are running. They may interleave reads/writes per node or they may not.

ActorDB does not allow reads while a write is in progress. It is quite possible we will optimize this part in the future as it is quite doable.

In FoundationDB you never had to think about splitting your dataset into something like your "actors". All transactions are independent and parallelizable, unless when they touch a common key - in which case one of the transactions is retried (optimistic concurrency).

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