[HN Gopher] Haydex: From Zero to 178.6B rows a second in 30 days
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Haydex: From Zero to 178.6B rows a second in 30 days
Author : pdubroy
Score : 49 points
Date : 2025-09-25 18:07 UTC (3 days ago)
(HTM) web link (axiom.co)
(TXT) w3m dump (axiom.co)
| dmitrygr wrote:
| 178.6e9rows/s/30days = 66150rows/s^2
| alexfromapex wrote:
| I usually just call it 178 billion
| gmueckl wrote:
| But only if your billion is 10^9, not 10^12.
| ccleve wrote:
| 178 billion? That's nothing. I did trillions just this morning. I
| went to the grocery store and picked an item off the shelf,
| effectively filtering out the trillions of other products that I
| could have picked but didn't.
|
| They did not process 178 billion rows per second. They did a
| search that found something in a large data set by eliminating
| the parts of the data set that could not have contained the item.
| Same way I did by picking one grocery store and going straight to
| the shelf.
| sally_glance wrote:
| Hm, if I understand their product correctly they are building a
| DB and their filtering actually returns correct results.
|
| So, the analogy doesn't really hold true unless you actually
| have these trillions of alternate products stored in your brain
| and manage to cite the matching subset on demand.
| Sesse__ wrote:
| Seemingly, their way of thinking goes roughly like this:
|
| If I have 10 billion rows in an SQL database, with a UNIQUE
| index, and do SELECT * FROM t1 WHERE pk=<number>, then I have
| "processed" 10 billion rows.
|
| If I do 10k of these queries per second, I have processed
| 100T rows per second.
| timhigins wrote:
| This kind of reads like an action or war novel
| twoodfin wrote:
| As edited by ChatGPT...
| rhaps0dy wrote:
| Yeah, it's very clearly LLM-edited, but it's fun to read. The
| LLM did a good job.
|
| It's not just a tech blog post - it's a thriller. ;)
| smartbit wrote:
| Write an adventure where we implemented _Bloofi
| Multidimensional Bloom Filters_ from this 2015 article
| https://arxiv.org/abs/1501.01941. At the end mention the
| second author, don't mention the algorithm nor that it is
| based on the 1970 Bloom-filter algorithm
| https://en.wikipedia.org/wiki/Bloom_filter. Make me the
| main character that did all the hard work and caused our
| customer to win. The adventure should be some 5000 words
| long and use each of these words 20-30 times: data, axiom,
| filter, query, hashcolumn, haydex.
| llllm wrote:
| Please share your prompt, was it 'tell HN I'm an asshole
| while flexing my fake tech creds'?
| jacquesm wrote:
| That looks like a variation on a Bloom filter to me.
|
| https://en.wikipedia.org/wiki/Bloom_filter
|
| In the 80's or so when I thought I was being really clever I came
| up with another variation on this and I recall being quite
| annoyed when someone on HN pointed out (many years later) that
| this was a staple of computing science for longer than that I had
| been busy with computers. So much for having original thoughts...
| tsenart wrote:
| Author here, indeed a variation of bloom filters:
| https://x.com/lemire/status/1971279371131646063
| jacquesm wrote:
| Ok. I have blocked X at the router level here since Elon went
| certifiable so I can't read that link but I will happily take
| your word for it.
| 1000units wrote:
| It's funny how this comment chain is about how names stick
| to ideas in somewhat arbitrary ways, and you are using
| "Elon" to explain a personal policy for information
| grooming.
| jacquesm wrote:
| I think 'don't give your data to assholes' is a pretty
| good policy, regardless of whether it is personal or
| business.
| teaearlgraycold wrote:
| It does go to show that a huge number of inventions we consider
| foundational are really just from a normal person being in the
| right place at the right time. When a field is emerging there
| is a lot of low hanging fruit you can get your name stamped
| upon.
| mrbluecoat wrote:
| Same EventDB as https://github.com/ahri/eventdb or proprietary?
| tsenart wrote:
| Proprietary.
| bluelightning2k wrote:
| This was very well written. Rare to see such spark in a tech
| write up.
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