Algolia Reviews & Product Details

The speed at which search results are returned.

It can get expensive if you have a large number of records, regardless of the search volume.

Our primary goal was enabling a search experience where the customer could search for products using natural language queries and one that could handle typos. Algolia allowed us to implement this without having to hire out for that expertise.

Very easy to implement. Created a search index for my Firestore database to introduce search in my Flutter app and had no problems whatsoever. Implementation (creation of the index, database export, database synchronisation and client implementation) took me less than half a day and it allowed me to introduce search with fast results in my product catalog.

Nothing at all. The solution Algolia provides was the complete package in my use case.

I was using a Firestore database for a product catalog and wanted to allow my users to search for products.

I worked on an iOS project with Algolia. It fetches the results super fast. Query settings are a bit tricky but once you figure out, it's super useful and customizable.

The way to set up differs version to version, so it sometimes unknowingly breaks if you blindly update.

Quickly search the DB with relatively straight settings. Refreshing as you type kind of thing is neat.

The documentation made my business rapidly build out functionality

the Support if you weren’t on a paid plan wasn’t super helpful.

Full text search (Firebase doesn’t support this - Algolia solution worked wonders)

How easy it is to setup a project and customize it to match the needs of the app

It may be a bit pricy for personal applications

Autocompletion feature is one of the main problems that Algolia solves.

The easy of integration and the speed of getting the responses. The documentation is also great. I have added a search feature to my personal blog, which is based on Jekyll. There is a Jekyll package that does all the heavy lifting, and for the parts to customize there is plenty of documentation. From the creation of the account to be up and running it took me less than one hour.

Nothing in particular. Everything was smooth and clean. I can't really say that there are downsides.

I wanted to add a search feature to my personal blog. I managed to do that in less than one hour, including the time necessary to create the account. One of the best parts of the Jekyll SDK I have used is that it automatically indexes all the posts in the blog, so I don't have to add anything. It integrated wonderfully with github, so it was really zero effort (and zero cost!) to have it up and running.

It's the easiest way to add search functionalities to your software, without having to worry about managing Solr or ES clusters. Their API is really well documented and easy to use. Pricing model is also easy and you should not have problems calculating how much you will end up paying. Other advantage is the low and consistent latency to all end users, with servers on every major continent, no user will have a bad experience.

It can be a lot more expensive than self managing a elastic search or other search software cluster by yourself.

We use it for searching pages on a blog, the main benefit is, as I mentioned, the ease of using the API, without having to worry about anything else. We also save a lot of time by not having to manage anything related to search.

We were comparing Search options for both our new website and our web based application focused on the families we serve. We explored options such as Elastic which provided a robust suite of tools. However, in the end we decided on Algolia for its hosted search, ease of implementation, and UX. It allows us to focus on our data and not have to worry about maintaining the Search experience.

Thus far in our implementation, we haven't had any complaints! Algolia provides with pretty much everything we need. It's almost like Stripe for Search!

We've been able to minimize the amount of time integrating this critical function of our web assets. We're able to focus on our data rather than maintaining the Search engine.

It was very quick and easy to install Algolia, and now our end users can quickly search our documentation to find the answers they seek. Praise has been expressions like "Algolia is incredible!", so we're very happy.

Unfortunately the open-source account doesn't always link things up correctly in Algolia's dashboard, which makes it slightly difficult to research specifics. I wish we could purge data before our official release date.

We added search to end-user documentation.

It makes up for Firebases' deficiencies!

Probably scaling up can be costly, but to start and prototype is great and easy

I was solving the search of Google maps businesses, taking into account the user location as well (to find closer shops)