Very well written article. I’d like some performance comparison aswell, because ElasticSearch can already do less than 20ms on a 100k documents, with each having more than 10 queries fields.
Eh, I’d assume the comparison isn’t flattering. I think the point of this article is to argue you don’t need ElasticSearch to implement a competent Full Text Search for most applications. Splitting hairs over a few milliseconds would just distract from that point, when most applications should be prioritizing simplicity and maintainability over such tiny gains in a reasonable dataset.
Might be interesting to try to analyze at exactly what point elasticsearch becomes significantly useful, however. Maybe at the point where it saves a full tenth of a second? Or where it’s returning in half the time? Could be an interesting follow up article.
Very well written article. I’d like some performance comparison aswell, because ElasticSearch can already do less than 20ms on a 100k documents, with each having more than 10 queries fields.
Of course, for simple sites, this is great!
The second part has some of this, but not as in depth as i’d like.
Eh, I’d assume the comparison isn’t flattering. I think the point of this article is to argue you don’t need ElasticSearch to implement a competent Full Text Search for most applications. Splitting hairs over a few milliseconds would just distract from that point, when most applications should be prioritizing simplicity and maintainability over such tiny gains in a reasonable dataset.
Might be interesting to try to analyze at exactly what point elasticsearch becomes significantly useful, however. Maybe at the point where it saves a full tenth of a second? Or where it’s returning in half the time? Could be an interesting follow up article.