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OkCupid Tech Blog

Company blog · tech.okcupid.comprogrammingweb

OkCupid Tech Blog is the company blog at tech.okcupid.com, writing about programming and web. Since 2015, 26 different Hacker News readers have linked it 46 times, most often “OkCupid Presents: Vespa vs. Elasticsearch for matching millions of people”. It is still writing: the last post was on 2025-04-23, and you can follow it by feed.

Visit the blog
46mentions?
26HN people?
2015–2022first – last linked?
Links on Hacker News per year · peak 14 in 2017

Too few sampled comments (4) to say how often HN recommends it.?

Why HN links it

HN commenters cite OkCupid's engineering blog as a reference for image hashing and perceptual matching, and for a Vespa vs Elasticsearch comparison. The comments link the posts without judging the writing.

Summarised by Claude from a sample of 4 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.

Most-linked posts?

  1. OkCupid Presents: Vespa vs. Elasticsearch for matching millions of people
    5 people · 5 mentions · first linked 2020-09-29
  2. Swiping Right on Bloom Filters
    4 people · 4 mentions · first linked 2015-12-01
  3. Evaluating Perceptual Image Hashes at OkCupid
    3 people · 3 mentions · first linked 2017-05-31
  4. The pitfalls of A/B testing in social networks
    3 people · 3 mentions · first linked 2017-04-18
  5. Moving OkCupid from REST to GraphQL
    3 people · 3 mentions · first linked 2020-11-13
  6. When Debuggers Lie by OkCupid
    2 people · 2 mentions · first linked 2017-07-14

What Hacker News says?

  1. we also have a tech blog that we are revitalizing! http://tech.okcupid.com

    Comment linking /

    on “Ask HN: Which companies have the best blogs written by their engineering team?”
  2. Submitted Why we decided against GraphQL for local state management as a story · 124 points

    HN discussion
  3. I think for handling truly/non-affine arbitrary transformations we will have to resort to ML. Then we could have matching very similar to how humans do it (where we really don't care if the transformation is affine/non-affine we just care if it's a huge transformation the makes the image unrecognisable). But I really don't know much about ML. Okcupid talked about this in an article about image hashing [0] and they h…

    Comment linking /evaluating-perceptual-image-hashes-okcupid/

    on “Show HN: Transformation Invariant Reverse Image Search”
  4. Submitted The pitfalls of A/B testing in social networks as a story · 124 points

    HN discussion
  5. We've had good success with Vespa [1] for this usecase, both using it to rank by vector similarity and apply business logic oriented filters. Search latencies are fairly low, even with constantly updating documents. [1] https://tech.okcupid.com/vespa-vs-elasticsearch-for-matching...

    Comment linking /vespa-vs-elasticsearch-for-matching-millions-of-people-6e3af18eb4dc

    on “A gentle introduction to vector databases”
  6. Submitted Evaluating Perceptual Image Hashes at OkCupid as a story · 97 points

    HN discussion
  7. Has anyone ever had success on an app like Hinge, then deleted it only to see a large drop in your success rate when nothing else changed about your profile? If so, it could be due to things like this: https://tech.okcupid.com/evaluating-perceptual-image-hashes-... Match Group owns OkCupid, Hinge, Tinder and so on.. so wouldn’t be surprising if they all used the same or similar algorithms for spam prevention and noo…

    Comment linking /evaluating-perceptual-image-hashes-at-okcupid-e98a3e74aa3a

    on “‘Why am I talking to 10 guys?’ The rise and fall of dating apps”
  8. Submitted Rust and RPC at OkCupid as a story · 63 points

    HN discussion
  9. Submitted A failed dating experiment – Responsiveness Sort as a story · 39 points

    HN discussion
  10. Submitted Moving OkCupid from REST to GraphQL as a story · 36 points

    HN discussion
  11. Submitted How OkCupid predicts who you will like as a story · 34 points

    HN discussion
  12. Submitted OkCupid Presents: Vespa vs. Elasticsearch for matching millions of people as a story · 11 points

    HN discussion
  13. Submitted How OkCupid organizes its multi-page React app as a story · 11 points

    HN discussion
  14. Submitted Evaluating Perceptual Image Hashes at OkCupid as a story · 8 points

    HN discussion
  15. Submitted When Debuggers Lie by OkCupid as a story · 7 points

    HN discussion
  16. Submitted Swiping Right on Bloom Filters as a story · 7 points

    HN discussion
  17. Submitted Building an Android Thin-Client at OkCupid as a story · 6 points

    HN discussion
  18. Submitted The pitfalls of a/b testing in social networks as a story · 6 points

    HN discussion
  19. Submitted Moving OkCupid from REST to GraphQL as a story · 4 points

    HN discussion
  20. Submitted Moving OkCupid from REST to GraphQL as a story · 4 points

    HN discussion
  21. Submitted Vespa vs. Elasticsearch for matching millions of people as a story · 4 points

    HN discussion
  22. Submitted Swiping Right on Bloom Filters as a story · 4 points

    HN discussion
  23. Submitted The Shadow Request: Troubleshooting OkCupid’s First GraphQL Release as a story · 3 points

    HN discussion
  24. Submitted An Intro Guide to Protocol vs. Object Oriented Programming as a story · 3 points

    HN discussion
  25. Submitted Monitoring performance the easy way: HAProxy to the rescue as a story · 3 points

    HN discussion
  26. Submitted Getting Hooked on React Hooks as a story · 3 points

    HN discussion
  27. Submitted When Debuggers Lie as a story · 3 points

    HN discussion
  28. Submitted iOS Scroll Performance Tutorial from OkCupid as a story · 3 points

    HN discussion
  29. Submitted Large-scale collaborative filtering to predict who will like you, with JAX as a story · 2 points

    HN discussion
  30. Submitted Vespa vs. Elasticsearch for matching millions of people as a story · 2 points

    HN discussion

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