12 points tatvamasi 2 days ago 8 comments

tilt_error 1 hour ago | parent

Isn't this the same as Elasticsearch searchable snapshots?

hmokiguess 1 hour ago | parent

Reminds me of turbopuffer

MattPalmer1086 1 hour ago | parent

Well, it answers the technical questions of what changes when you stick your search indexes on slower and more expensive storage - but not why you would do that in the first place.

appcustodian2 37 minutes ago | parent

it's web scale!

deathanatos 32 minutes ago | parent

> On a local SSD, a random read costs nothing if a page is cached, and costs under a millisecond in case of a page fault. […] The scarcest resource is not CPU, and not bytes, but the number of round trips you make to the object store, and most design decisions below follow from that

There's not really a difference here between S3 and your disk, aside from the literal amount of latency. Restructuring the format to require less reads to make S3 faster would proportionally benefit disk reads.

S3 is a lot easier manage, though. Storage is just then AWS's problem. (And what's a few ms of latency on the BE when pages take tens of seconds to load on the whole.)

elendilm 9 minutes ago | parent

> There's not really a difference here between S3 and your disk, aside from the literal amount of latency.

Latency is the whole point.

jonathanstrange 14 minutes ago | parent

How about not putting it on S3?

elendilm 5 minutes ago | parent

Appreciate the strategies that went into the work to optimize a high latency foundation to feasibly work as a search index.

Our own work and stack goes against this specific architecture fundamentally. Were I to make one, where scalability and efficiency for a search index is prioritized, I would approach it more from a regionally distributed hierarchical fractal architecture where caching is leveraged at every layer.

But architectures like this puts strong constraints on the solution space which is how exceptional insights and breakthroughs happen.