
Algolia raises $110M for its search-as-a-service - sfg75
https://techcrunch.com/2019/10/15/algolia-finds-110m-from-accel-and-salesforce-for-its-search-as-a-service-used-by-slack-twitch-and-8k-others/
======
mlthoughts2018
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 engineers you probably thought you could avoid hiring by outsourcing to
Algolia / Rekognition in the first place.

But once you need to hire them anyway, you might as well utilize them to build
this type of thing in-house in ways that are much more tailored and optimized
around your in-house data models and data integration tools.

To put in perspective, I’ve worked in several companies (from small start-ups
to large ecommerce sites) that have a variety of search needs spanning plug
and play Lucene all the way to highly customized joint embedding neural
network based nearest neighbor search, and tons in between.

The distribution of text in e.g. the support center search use case was
totally different than the product search use case or the document store use
case, where highly unique word distribution, special words, frequency of
required updates to the search index, asymmetric costs of surfacing bad or
deleted content items, etc., was the norm.

Every search use case was different and needed care to develop unique
annotated result sets to measure mean reciprocal rank, NDCG, etc., as well as
simple stakeholder subjective opinion of quality.

Short of basically hiring Algolia to be a gigantic consultant on all these
things, I don’t see how it could actually be valuable.

I suspect it’s just an easy sell to CTO types that don’t really understand.
They want “search” to be one problem with one little component to drop in to
solve it, but it’s just not real.

~~~
apalmer
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, and no clue how to assess and hire
individuals who could implement it, and no clue how to find and hire a cio who
could put together a team from scratch who could do this on a reasonable
timeline.

~~~
mlthoughts2018
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 Rekognition, is that if you ship
off your data and the third party trains some model (most likely fine-tuning a
base model), then you’re done, problem solved.

Even for businesses where search is not a core part of their direct value
proposition to customers this is flagrantly untrue.

~~~
hnaccy
>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.

You just have to pay Algolia, wire up the APIs, and then see if whatever
stakeholder that was complaining about search stops complaining. If they do
then it's good enough.

~~~
mlthoughts2018
Totally false. This is like massively overfitting a high-order polynomial
regression to your data. The fit looks good enough, then the next data point
comes in and breaks in a way the existing model cannot be hacked to account
for.

The search results you believed were implicitly tuned to some feedback
mechanism slowly experience creep as the customer cohort changes and data
distribution changes until before you knew it your management of the search
solution is a ceaseless game of whack-a-mole siphoning off engineering
resources at a rapidly increasing rate. It’s the same false promise of just
having some engineers stand up Elastic Search.

~~~
aphroz
Not all decisions are good decisions, it depends on who makes the call. In
most cases, someone ask you to use a solution because it looks/feels better.
In this case Algolia showed how fast and how well it could be implemented.
Once the person who takes the decision is convinced it will be implemented.
It's mostly marketing. Probably less than 1% of all e-commerce websites
measures the impact of a decision.

~~~
mlthoughts2018
I did say as much in my original post: Algolia and Rekognition are marketed at
CTOs and directors of engineering who want to be sold on a magical line item
that removes a whole concept area from their concern, especially one
associated with the difficulty of hiring and affording good machine learning
staff who can work on the problem both pragmatically and theoretically. They
want to be sold a story.

I will say though that your 1% claim is way off in my experience (which
includes 3 medium and large ecommerce companies). These companies employ
armies of product managers and analytics staff that measure the shit out of
everything from the color of a button to the size of font in a banner display
for a discount promo code. These things aren’t usually measured because they
find value, rather just to give the appearance of data driven decision making
and justify job perpetuity.

------
adventured
It's interesting to see this valuation on search as a service, given the
leader, Elastic, is in obvious valuation trouble. The market is unimpressed:
the Elastic stock hasn't net moved higher since mid January (so most of the
time they've been public).

Just take a look at the actual business performance of Elastic.

$271m in sales for the last fiscal year. Negative $101 million operating loss.
Pretty bad, although not extremely unusual for SaaS companies in high growth
mode. So there must be great growth going on, right? No.

They added a mere $9m in sales last quarter. $89m in sales with a $42m
operating loss (whoa). They added an additional $10m in operating loss and
gained a mere $9m in sales.

So if they can keep up that rate of growth, they might generously add $45-$50
million in sales this year. Maybe 16%-18% growth for a company bleeding red
ink, that isn't particularly large in terms of sales yet (ie they're
struggling to generate fast growth at a small'ish scale). And all that needs
to support trading for 20 times sales on a business that is a decade old and
has never produced a profit.

Either they find a lot of growth soon or in the next market down cycle Elastic
is worth 1/3 to 1/2 of what they're trading for now. The same will probably go
for their lesser peers. The clock is starting to tick hard on these extreme
valuations (hello WeWork, Uber, Lyft).

~~~
2arrs2ells
Maybe Elastic isn't growing because Algolia is eating their lunch?

~~~
AznHisoka
elastic isn’t competing with algolia, imo. elastic is after the enterprise
customers who have a mission-critical need for search (rather than a casual
need like algolia users)

but I think mission-critical search is a niche technical problem that isn’t
applicable to many enterprises.

~~~
donretag
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.

~~~
xapata
Thus the change of name, dropping "search".

~~~
baud147258
elastic is the parent company that's developping elasticsearch and the
associated tools (logstash, kibana, *beats…)

------
faceshapeapp
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.

~~~
sniperjzp
It feels ironic, I searched "Algolia" from both, today's news is ranked as #7
in Algolia powered HN. From Algolia:
[https://imgur.com/a/atRMnwj](https://imgur.com/a/atRMnwj) From Google:
[https://imgur.com/a/d3EKdUp](https://imgur.com/a/d3EKdUp)

Some people says it's popularity based, but if I change it to date based, it's
broken? [https://imgur.com/a/HGzL6fO](https://imgur.com/a/HGzL6fO)

~~~
faceshapeapp
Simply sorting by date doesn't really seem to be that useful either.

For example, the poster below showed the following link for the "ml" query:
[https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...](https://hn.algolia.com/?dateRange=all&page=0&prefix=true&query=ml&sort=byDate&type=story).

If you look at the results, the first 2 results only matched part of the
poster's username and many of the top results here are empty threads which are
not that useful since HN is mostly for discussions.

To be clear, I'm not saying it's all bad, just pointing out that there are low
hanging fruits which can improve results quite a bit.

Also, Algolia seems misspelled in your query which is why it fails when
reordering by date:
[https://imgur.com/a/pO9fBWr](https://imgur.com/a/pO9fBWr), it works
otherwise. Although, it says the date is 1 day old when it's just 2 hours old.

~~~
sniperjzp
️ oops, a typo in the query, but why they have query correction for popularity
based, not date based?

~~~
redox_
Yes, when sorting by date it's currently configured to disable typo-tolerance.
This is to avoid having an old (but approximative, like with typos) result
BEFORE the correct ones.

------
Game_Ender
Their DocSearch program for open source projects is really great [0]. Check
out the Jekyll docs [1] instant results that usually find just what you want.
My only complaint is I want a plugin and play solution I can deploy for
private internal documentation websites.

0 -
[https://community.algolia.com/docsearch/](https://community.algolia.com/docsearch/)

1 - [https://jekyllrb.com/docs/](https://jekyllrb.com/docs/)

------
goertzen
Congrats to the whole Algolia team.

I can’t think of any SaaS business that invested in, and executed such a
smooth onboarding and retention ecosystem.

I’ve used them for small sites and large enterprise clients (10B+) and I’ve
always felt like I’ve got way more than I’ve paid for.

PSA: Algolia has basically hidden a category making/taking over strategy in
plain sight.

------
dennisgorelik
Hacker News generates 86.10% of referral traffic for algolia.com:

[https://www.similarweb.com/website/algolia.com#referrals](https://www.similarweb.com/website/algolia.com#referrals)

------
Deimorz
Official blog post: [https://blog.algolia.com/algolia-
series-c-2019-funding/](https://blog.algolia.com/algolia-
series-c-2019-funding/)

------
mc3
Incase someone doesn't know already: they have a HN search too!
[https://hn.algolia.com/](https://hn.algolia.com/)

~~~
a_imho
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.

~~~
redox_
Yes, when sorting by date it's currently configured to disable typo-tolerance.
This is to avoid having an old (but approximative, with typos) result BEFORE
the correct ones.

~~~
mc3
Ah the old multi-factor sort problem. Fun figuring out how to handle those
scenarios in Elastic Search too (or more generally any sorting UI). For
example you want traditional Chinese food near you. What is better -
traditional Chinese food 14km away or fusion 2km away? Well that depends on
the wetware, but you have to guess what the user would want.

------
mjfern
What underlying tech does Algolia use? Elastic search?

~~~
winrid
They built their own. The engine is baked into nginx modules.

[https://blog.algolia.com/?filter=engineering](https://blog.algolia.com/?filter=engineering)

------
tschellenbach
Amazing product and team. Nicolas still finds time to help small startups like
us. Their success is well deserved.

------
im_cynical
I was just looking for a site search solution three days ago for a side
project I'm working on. I found Elastic's offering but found the lack of a
free tier(no 14-day trail crap) off-putting. I'll give these guys a try. Grats
on the raise!

------
rvanmil
Does anyone know how MongoDB’s new search engine[0] compares to Algolia?

[0] [https://www.mongodb.com/atlas/full-text-
search](https://www.mongodb.com/atlas/full-text-search)

~~~
lovelearning
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.

------
rajacombinator
Congrats to them but I find the product to perform quite poorly on HN. Seems
to do some kind of fuzzy matching / weird relevance ranking and not full
indexing when all I really want is a full index text search.

~~~
sjg007
HN search should be parameterized by the user, where they've commented and
what they've clicked on. The last part is why outsourced search performs
poorly. They can measure what you click on in their search results but I doubt
they know what you clicked on HN.

------
vast
Side question: how interesting and flexible is algolia as a replacement of a
custom solr setup? I don't like the HN search and never heard that it is in
use for larger data sets.

~~~
redox_
You should give it a try; Algolia has a FREE tier you can play with. You can
also watch this 45sec video to get a grasp of it:
[https://youtu.be/IYY5RM1sBC0](https://youtu.be/IYY5RM1sBC0)

------
factsaresacred
If you've ever tried installing ElasticSearch and then switched to Algolia
you'll understand how great of a product it is.

Now if Firebase could only buy them out and add decent search to their suite
of products that would be swell. Mind boggling that Firebase - part of Google
- still lacks a decent search solution.

------
cloudking
Are there any good open source alternatives?

------
sbmthakur
There is a discussion on Stackshare(a bit old) about the tech they are using:

[https://stackshare.io/posts/how-algolia-built-their-
realtime...](https://stackshare.io/posts/how-algolia-built-their-realtime-
search-as-a-service-product)

------
orliesaurus
Long time since those days in a tiny office in Rue du Sentier with
Efounders...congrats folks!

------
rwmj
I wonder if they can use the money to fix it so it works without Javascript?

------
jmkni
Nice work.

The homepage is great from a developer perspective, select your backend on the
left, frontend on the right, and you get an idea right away of what a basic
implementation looks like. Very clever.

------
cityzen
I figure with the ramped up marketing blitz they’ve been on we will be hearing
about their IPO soon.

