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Algolia raises $110M for its search-as-a-service

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Re: Algolia raises $110M for its search-as-a-service

#71

Post by cjblomqvist »

newscracker wrote: post #65
faceshapeapp wrote: post #2

Congrats to the team! Although, am I the only one who finds that searching HN through Google gives better results than searching it through the Algolia powered HN search? For example, search "ml" in both, Algolia results are years old and don't seem that relevant, whereas Google picks up more recent threads.

I came to this discussion just to say something similar. Algolia doesn’t seem to be great for HN, and off late I see it not loading search results (maybe something to do with my network, browser and the site) or being quite slow compared to say, Google Search.

Another data point: Have encountered the same problem.

Re: Algolia raises $110M for its search-as-a-service

#73

Post by ehnto »

mlthoughts2018 wrote: post #21
apalmer wrote: post #19

Earlier quoted context omitted.

You are absolutely factually correct in your analysis, but you are completely missing how business works. Fundamentally, there is value to most businesses in being able to just buy a decent solution to a non core competency. That’s where Algolia and AWS and basically all service companies come in... a medium scale clothing manufacturer with a booming e-commerce site may well know they have no clue how to do search, a…

I’m saying in my experience there is no such thing as one singular “decent solution” for search. It varies enormously from use case to use case, customer cohort to customer cohort, etc. To even know if you’re buying a decent solution from Algolia or not, you’d already have to hire pretty much all the same staff you’d have to hire to more cost-effectively build it in-house. I think the fundamental myth, just like with…

I am not trying to be flippant, but maybe you are misunderstanding what Algoia provides?

Let's say I have an eCommerce platform. The search provided by the framework is slow and I want to put together an instant search feature. It's too slow, and I don't have a search specialist to speed it up. So I add the Algoia plugin to the platform, sync my products and the work is done. Literally, real world example, install the plugin and suddenly my archaic eCom platform has instant search. Not only that, but I can manage the search result weigths and preferences from within Algolia with no special experience. My existing search couldn't do that.

I am not sure where you would need an ML specialist in any of this, certainly not a whole team. For most people Algolia out of the box is plenty.

Re: Algolia raises $110M for its search-as-a-service

#74

Post by lovelearning »

rvanmil wrote: post #69

Does anyone know how MongoDB’s new search engine[0] compares to Algolia? [0] https://www.mongodb.com/atlas/full-text-search

Not an exhaustive list, but important differences off the top of my head:

- End-to-end search:

Algolia's offerings span both front-end (InstantSearch drop-in widgets) and back-end (actual search API). Simple applications can be built without ever talking to Algolia API at all because their widgets do it for you.

Atlas is all back-end - just a DB service with FTS on the side; left to you to integrate front-end.

- Configuration:

Algolia's dashboard GUI is where a lot of the configuration is done. Some configurations are not available at all via APIs. It's relatively simple.

Atlas requires more JSON-type configuration entries, and some knowledge of Lucene internals.

- Text analysis:

Algolia text tokenization pipeline is mostly a black-box but works fine most of the time. It exposes only a few settings like ascii-folding. It's fine for normal dictionary words, but has problems with domain-specific text (for example, people/place names, scientific terms, etc).

Atlas exposes many aspects of Lucene's analysis pipeline, but it does require knowledge of Lucene.

- Multilingual support:

Algolia supports all its features for ~70 languages.

Atlas analysis has to be configured separately for each language.

- Query syntax:

Algolia defaults to simple queries but the API supports a more complex query syntax with boolean operators and such.

Atlas has its own JSON query DSL that's related to Lucene's query syntax capabilities.

- Faceting:

Algolia faceting configuration and API are far simpler than Atlas's DSL.

Re: Algolia raises $110M for its search-as-a-service

#75

Post by Redsquare »

atombender wrote: post #15
Redsquare wrote: post #10

Earlier quoted context omitted.

It's only as good as the HN team have configured the ranking and other algolia settings. Be nice for them to expose these.

Pretty sure HN's search is implemented by Algolia themselves. It's served from algolia.com.

You cant self host algolia

Re: Algolia raises $110M for its search-as-a-service

#77

Post by mrweasel »

Rapzid wrote: post #67
donretag wrote: post #61

Earlier quoted context omitted.

Elastic is not even after the search market, but the analytics/loggin/reporting sector. Of course, they are after every customer, but one Elastic rep told me that 75% of customers are not using Elasticsearch for traditional search.

Then they are in huge trouble because Kibana is hot garbage. Nearly zero of the user experience goodness from Kibana3 has survived the Elastic aqui-hire.

If they plan to compete with Splunk they need do some serious rework of Kibana. Even something relatively new like Humio is must easier to work with than Kibana.

Entire ELK stack was always pretty bad, compared to Splunk or a syslog server and grep, in my opinion.

We tried to buy a support contract from Elastic years back, but the pricing model put all useful levels of support way beyond our reach. Apparently they didn't understand that we had to make our money and didn't have VC funding.

Re: Algolia raises $110M for its search-as-a-service

#78

Post by jackdh »

mlthoughts2018 wrote: post #12

I’ve always had a hard time understanding the value proposition in the same way I don’t understand the value proposition of e.g. AWS Rekognition. Paying per use certainly doesn’t make sense, because it has to be qualified by the accuracy you get per use. And there’s no serious way to understand the accuracy you get per use (on your specific unusual distribution of queries) without employing the expensive ML / stats e…

Another big difference here is that Algolia does not use machine learning in its algorithms.

This according to an old friend who worked there allowed them to really drill down to why which search results are shown and hence the pay per use does actually make sense.

Re: Algolia raises $110M for its search-as-a-service

#80

Post by a_imho »

mc3 wrote: post #41

Incase someone doesn't know already: they have a HN search too! https://hn.algolia.com/

search for e.g 'microsoft' -> ~120k results

change sort by popularity to sort by date -> ~30k results

I don't really understand how sorting can affect the number of results. Btw youtube search does this too.

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