21–30 of 111 posts
I've actually been avoiding using Algolia after I used IndexTank and then they were acquired by LinkedIn. (I always said grats diego + team at IndexTank) but it was a frustrating experience to need to role up everything and pack up shop. Seeing a huge raise like this actually makes me feel better about the possibility of using Algolia rather than rolling my own Solr containers.
We're using Algolia (the free version) for all Facebook open source project websites (React, GraphQL, Yarn, ...) and it's been nothing short of awesome. You just include a js file and add an input where you want the search and it just works(tm). It has required 0 maintenance, it didn't go down, the api didn't change, nothing to tweak on the backend... Users have gotten a quality and super fast search since then. I hi…
Reading this I get the impression that they do the indexing themselves or something but in the Quick Start the first thing you need to do is importing your data. What am I missing?
Just their typo acceptance alone makes Algolia, imo, the best 3rd party search service available currently.
Oh, that's the Hacker News site search... Works fine for me, except I always switch from "results by Relevance" to "Results by date", as in "Has this been posted already...?" Did not know Google is discontinuing its custom search engine. Looks like there may be a business opportunity here.
You can switch to experimental UI.
Anyone care to share positive and negative experiences of using Algolia to power search in your SaaS? (We're currently using MySQL's full-text search and are finding it to be a long way short of the experience we'd like our customers to have.)
Let me know if you wanna know more!
I definitely love the hn search which is powered by algolia. Fast and instant. I wish it was possible to turn off fuzzy matching in some cases.
What I notice with their results is that they start strong, but fall off very rapidly into partial gibberish.
For example, say I want to make a battery-powered project. I search "lipo." The results start out promising; charging boards, including a few options tailored to specific popular boards. But by the time we get to the end of page 1, only every other result or so is actually relevant. Useful results like batteries and connectors are interspersed with random microcontrollers, LEDs, motors, etc.
Still, it works and you can always refine by category if that sort of thing really bothers you. It seems like a pretty solid solution, and the issues I'm mentioning are probably caused by the implementation, which I'll bet uses the full text description of entries to weight things towards not excluding a potentially-relevant result.
We're using Algolia (the free version) for all Facebook open source project websites (React, GraphQL, Yarn, ...) and it's been nothing short of awesome. You just include a js file and add an input where you want the search and it just works(tm). It has required 0 maintenance, it didn't go down, the api didn't change, nothing to tweak on the backend... Users have gotten a quality and super fast search since then. I hi…
> You just include a js file and add an input where you want the search and it just works(tm). Reading this I get the impression that they do the indexing themselves or something but in the Quick Start the first thing you need to do is importing your data. What am I missing?
If you have any other usecase than technical documentation, we recommend indexing your data through the API.
Ben
I've actually been avoiding using Algolia after I used IndexTank and then they were acquired by LinkedIn. (I always said grats diego + team at IndexTank) but it was a frustrating experience to need to role up everything and pack up shop. Seeing a huge raise like this actually makes me feel better about the possibility of using Algolia rather than rolling my own Solr containers.
However, the market is very very tough here.
The problem here is consolidation: all big customers (successful websites) will end up being part of mega-corporations (Amazon, Microsoft, Google, Salesforce, etc.). And all these companies have their own search engine (which they use for other machine learning, etc. - not just search). For example, Twitch will probably switch to Amazon A9.
So the question here is: what is the game plan to return this $53M? Acquisition?