These days, I get to know new services only when they get acquired.
Algolia Acquires Search.io
31–40 of 49 posts
Re: Algolia Acquires Search.io
#32Note: I work on Typesense [1], an open source alternative to Algolia. This is an interesting acquisition from my perspective because we also just started working on adding vector search to Typesense about a month ago. So you can now do nearest neighbor searches by bringing your vectors into Typesense. This lets you do things like similarity searches, recommendations, etc. I’d love to have more beta testers use the fe…
Typesense is so good (and affordable!). I'm so thankful y'all are providing an alternative to Algolia.
It feels similar to Render vs Vercel where clearly players like Vercel & Algolia make the big bucks from enterprise clients and thus make their services less accessible to small companies like mine.
Quick question with regards to vector search, do y'all intend on exposing some basic embedding service to your platform? I think it'd be pretty powerful to add a basic word2vec embedding model so that users who want to play around with vector search can simply just send some text and typesense would do the rest (convert text to embedding, index embedding, etc).
Re: Algolia Acquires Search.io
#33Note: I work on Typesense [1], an open source alternative to Algolia. This is an interesting acquisition from my perspective because we also just started working on adding vector search to Typesense about a month ago. So you can now do nearest neighbor searches by bringing your vectors into Typesense. This lets you do things like similarity searches, recommendations, etc. I’d love to have more beta testers use the fe…
Thank you very much for working on Vector Search. Looking forward trying it out as soon as it gets stable. Thanks again!
Re: Algolia Acquires Search.io
#34Note: I work on Typesense [1], an open source alternative to Algolia. This is an interesting acquisition from my perspective because we also just started working on adding vector search to Typesense about a month ago. So you can now do nearest neighbor searches by bringing your vectors into Typesense. This lets you do things like similarity searches, recommendations, etc. I’d love to have more beta testers use the fe…
Typesense is so good (and affordable!). I'm so thankful y'all are providing an alternative to Algolia. It feels similar to Render vs Vercel where clearly players like Vercel & Algolia make the big bucks from enterprise clients and thus make their services less accessible to small companies like mine. Quick question with regards to vector search, do y'all intend on exposing some basic embedding service to your platfor…
Yes, we plan to do that, but we will start off with first supporting raw vector data type and search on that.
Re: Algolia Acquires Search.io
#35Note: I work on Typesense [1], an open source alternative to Algolia. This is an interesting acquisition from my perspective because we also just started working on adding vector search to Typesense about a month ago. So you can now do nearest neighbor searches by bringing your vectors into Typesense. This lets you do things like similarity searches, recommendations, etc. I’d love to have more beta testers use the fe…
We're currently A/B testing TypeSense and Algolia, but the pricing model difference alone makes me almost want to skip the whole process and just go with TypeSense. Algolia's price per search model is a little ridiculous for people building UIs with live search.
Re: Algolia Acquires Search.io
#36some interesting points from this other piece "While the acquisition price was undisclosed, media reports suggest Algolia paid more than $100 million for Search.io" https://www.businessnewsaustralia.com/articles/french-unicor... "Search.io’s mission is to “enable every organization to build smart search and discovery solutions.” The company was founded in 2014 by Hamish Ogilvy and David Howden (originally named Sajar…
Vector search is incredibly powerful on matching on context or similarity. For example, automobile and car are semantically similar and, and one will rank well for the other in a search. Vector search, though, isn't as good on handling typos and not good at all when it comes to as you type searching. Vehic won't match on auto, for example. We believe that there is use for each of these approaches and a use in a singl…
I'd like to add that vector search works not just for natural language, but also for a variety of other types of unstructured data as well. Images, video, user profiles, and pretty much anything else that can be vectorized. Here's an example of image search: https://milvus.io/docs/image_similarity_search.md
Re: Algolia Acquires Search.io
#37Does this improve or impact docsearch?
Re: Algolia Acquires Search.io
#38I've been interviewing users of vector search and am cataloguing my findings in this repo:
https://github.com/esteininger/vector-search
feel free to watch for updates :)
Re: Algolia Acquires Search.io
#39Earlier quoted context omitted.
Do yall have a technical blog? I would love to both understand the problem and methods, domains yall cross (eg biometrics and fuzzy matching?), and how yall integrate in different industries. A good search partner is hard to find. PageRank is fun and all, but I believe better methods exist these days.
Here's a link to our engineering blog posts: https://www.algolia.com/blog/engineering/ And our CTO, Julien, wrote an "Inside the Engine" series on how our search engine works. It doesn't have the new "hybrid search" but it shows you the base of how we do search: https://www.algolia.com/blog/engineering/inside-the-algolia-...
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Re: Algolia Acquires Search.io
#40Note: I work on Typesense [1], an open source alternative to Algolia. This is an interesting acquisition from my perspective because we also just started working on adding vector search to Typesense about a month ago. So you can now do nearest neighbor searches by bringing your vectors into Typesense. This lets you do things like similarity searches, recommendations, etc. I’d love to have more beta testers use the fe…
Any books / papers you would recommend to cover basics of search engine implementation? Practicalities like elias fano encoding and WAND searching.