4 ms·

All great and good to be very fast, but at what price? From their page it costs $450 for 5mil records. In the search world, this is nothing. So I guess its g

All great and good to be very fast, but at what price? From their page it costs $450 for 5mil records. In the search world, this is nothing. So I guess its going to come down to if your company is at the point where they need to shave off 1-200ms for hundreds of dollars a month. Second, I would wait and see how their reliability hashes out before I rely on them for any production services.

jlemoine 13y ago
The search world is very big :) 5 mil records is nothing if you index logs (which is not Algolia typical use-cases) but for example this is big from an e-commerce perspective.
- johnnymonster 13y ago
  In the e-commerce world, the difference between 2ms and 200ms isn't that big of a deal. Search relevance, however, might be something that is important. It looks like that is something they are focusing on heavily.
  - jlemoine 13y ago
    200ms does not allow you to provide search-as-you type and our e-commerce customers see that performance is linked to conversion. In term of relevance, we have developed a ranking algorithm specialized on that case that provide better results than traditional approach: http://blog.algolia.com/search-ranking-algorithm-unveiled/ http://blog.algolia.com/search-ranking-algorithm-unveiled/
    - arghbleargh 13y ago
      Your algorithm seems OK, but what was the "traditional approach" that you compared it to, and how did you compare them? It seems like you actually gain a lot from full document search (e.g. products with multi-paragraph descriptions). Otherwise, you might as well just do a SQL query to get your results.
      - jlemoine 13y ago
        By traditional approach we means all engines that use a unique score to rank documents (like all engine based on Lucene). SQL queries are not relevant for text query, for example you have no notion of tokenization or proximity between words. We plan to write a blog post on limit of SQL based search.
  - kwi 13y ago
    Ahaha, speed is huge deal for e-commerce. It has already been proved enough by big merchants tests. Search relevance is too! The key is to have them both at the same time :)

jlemoine 13y ago

The search world is very big :) 5 mil records is nothing if you index logs (which is not Algolia typical use-cases) but for example this is big from an e-commerce perspective.

johnnymonster 13y ago
In the e-commerce world, the difference between 2ms and 200ms isn't that big of a deal. Search relevance, however, might be something that is important. It looks like that is something they are focusing on heavily.
- jlemoine 13y ago
  200ms does not allow you to provide search-as-you type and our e-commerce customers see that performance is linked to conversion. In term of relevance, we have developed a ranking algorithm specialized on that case that provide better results than traditional approach: http://blog.algolia.com/search-ranking-algorithm-unveiled/ http://blog.algolia.com/search-ranking-algorithm-unveiled/
  - arghbleargh 13y ago
    Your algorithm seems OK, but what was the "traditional approach" that you compared it to, and how did you compare them? It seems like you actually gain a lot from full document search (e.g. products with multi-paragraph descriptions). Otherwise, you might as well just do a SQL query to get your results.
    - jlemoine 13y ago
      By traditional approach we means all engines that use a unique score to rank documents (like all engine based on Lucene). SQL queries are not relevant for text query, for example you have no notion of tokenization or proximity between words. We plan to write a blog post on limit of SQL based search.
- kwi 13y ago
  Ahaha, speed is huge deal for e-commerce. It has already been proved enough by big merchants tests. Search relevance is too! The key is to have them both at the same time :)