Notes

In this section, we’ll add full-text search with Algolia, Flutter, and Firebase to our eCommerce app.

When implementing full-text search, we need to consider a few things:

• how to implement a good UX
• how to add caching and debouncing (so that we don’t make too many API requests to the server)
• how to deal with realtime updates and pagination

What we will cover in this section

• Overview of all the Firebase extensions that we can use to implement full-text search
• How to create an Algolia app and configure a search index
• How to install and configure the Algolia extension so it can index the products data in Cloud Firestore
• Adding Algolia to our Flutter client app (API keys setup + basic search implementation)
• Optimizing our implementation and by adding caching, debouncing and realtime updates

By the end, we’ll have a robust and cost-effective full-text search implementation that is powered by Algolia.

As usual, we’ll use a modular architecture that could be adapted to use any kind of server-side search API (other than Algolia).