go-memdb VS tailetc

For another in-memory database example, you could also check out https://github.com/hashicorp/go-memdb, but it's based on a radix tree implementation.

I just think its a glorified map. Yeah, for example go-memdb list some of its advantages in their https://github.com/hashicorp/go-memdb/blob/master/README.md README. But it is not clear whether you gain any performance gain over a map except for avoiding the locking as explained.

>So we invested what probably amounts to two or three weeks of engineering time into designing in-memory indexes that are transactionally consistent

I'll be interested to see that part if it does get open sourced. I've used https://github.com/hashicorp/go-memdb which sounds similar.

https://github.com/tailscale/tailetc/blob/b2fa539c2383d30d03e0eea1052022af132dca9f/tailetc.go#L142

Interesting choice of technology, but you didn't completely convince me to why this is better than just using SQLite or PostgreSQL with a lagging replica. (You could probably start with either one and easily migrate to the other one if needed.)

In particular you've designed a very complicated system: Operationally you need an etcd cluster and a tailetc cluster. Code-wise you now have to maintain your own transaction-aware caching layer on top of etcd (https://github.com/tailscale/tailetc/blob/main/tailetc.go). That's quite a brave task considering how many databases fail at Jepsen. Have you tried running Jepsen tests on tailetc yourself? You also mentioned a secondary index system which I assume is built on top of tailetc again? How does that interact with tailetc?

Considering that high-availability was not a requirement and that the main problem with the previous solution was performance ("writes went from nearly a second (sometimes worse!) to milliseconds") it looks like a simple server with SQLite + some indexes could have gotten you quite far.

We don't really get the full overview from a short blog post like this though so maybe it turns out to be a great solution for you. The code quality itself looks great and it seems that you have thought about all of the hard problems.