Live data from Hacker News

Ex-Googlers CockroachDB: A Scalable, Geo-Replicated, Transactional Datastore

github.com

51–60 of 70 posts

Re: Ex-Googlers CockroachDB: A Scalable, Geo-Replicated, Transactional Datastore

#53
post #18

Are there distributed data stores like this that are also resilient to intentional sabotage? I've been looking recently at long-term digital preservation systems -- tools designed to archive large amounts of data for decades. This is the Library of Alexandria problem -- how do we preserve all this data we're generating against once-in-a-century disasters? So this 2005 paper lists thirteen different threats to long-te…

Any idea how well LOCKSS would handle this?

http://www.lockss.org

http://blog.dshr.org/2014/07/trac-certification-of-clockss-a...

Re: Ex-Googlers CockroachDB: A Scalable, Geo-Replicated, Transactional Datastore

#54

It's really strange to see networked databases go through this iterative design fad. It was file transfers back in the 90s/00s; everyone had their own distributed decentralized file transfer solution. Little known fact, Gentoo's Portage almost became an internet-wide distributed decentralized public file system. Thank god they abandoned that idea. Can you imagine trying to debug a file transfer error just to get an m…

> Little known fact, Gentoo's Portage almost became an internet-wide distributed decentralized public file system.

Am I the only person really sad that this didn't happen? after using apt over Tahoe-LAFS (over I2P - KillYourTV's PPA is on clearnet and I2P), I wanted this to be the default behavior for apt.

Re: Ex-Googlers CockroachDB: A Scalable, Geo-Replicated, Transactional Datastore

#55
post #36

Happy to see it's written in Golang.

As a Go developer I was happy as well. On the other hand this question immediately popped into my mind: What kind of overhead does the GC incur, and how does it affect processes like a database where low latency is desired?

If I had to guess, I would say network and disk I/O will be the bottlenecks. Disk I/O less so because distributed system, and SSD. I imagine if anyone can solve GC issues, though, I would bet on Google :)

Re: Ex-Googlers CockroachDB: A Scalable, Geo-Replicated, Transactional Datastore

#57
post #2

Why the 'Ex-Googlers' in the title. Is it like a seal of approval or something?

I was kind of put off by this as well. Does where they worked in the past have anything to do with how useful the project is now or how talented the people are? What if they're doing it on their own because Google thought the project was useless? What if they were fired from Google, or only worked at Google for a month? How does the founders' past involvement with Google mark this project as any more interesting than any other random "Show HN" project?

Re: Ex-Googlers CockroachDB: A Scalable, Geo-Replicated, Transactional Datastore

#59
post #29
post #21

Earlier quoted context omitted.

Does it? I don't think ex-Googlers gives anything of value here.

It indicates that the project is worth a closer look rather than waiting or dismissing it outright.

> It indicates that the project is worth a closer look rather than waiting or dismissing it outright. reply

I'm curious, could you explain why? Google is an incredibly large company with many developers who never even touch their data systems so to me saying ex-Googler really doesn't mean anything beyond that they're probably a senior developer considering how rigorous (and honestly some old hat) their interview process is. But that doesn't change my viewpoint of the project at all.

Re: Ex-Googlers CockroachDB: A Scalable, Geo-Replicated, Transactional Datastore

#60
post #36

Happy to see it's written in Golang.

As a Go developer I was happy as well. On the other hand this question immediately popped into my mind: What kind of overhead does the GC incur, and how does it affect processes like a database where low latency is desired?

What kind of overhead does the GC incur, and how does it affect processes like a database where low latency is desired?

The eventual goal (golang v1.5 IIRC) is to have 40ms out of every 50ms available for actual processing. This is the kind of 'soft real time' that should provide good responsiveness for most clients most of the time.

Post reply on HN