How to Watch an Entire Firestore Collection?

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Google’s Firebase has been getting more and more popular over the past few years. Firebase lets developers make applications that can grow quickly and have real-time databases.

As Google’s top NoSQL cloud database solution, Cloud Firestore is included in the package. One of the most interesting things about the database is that your frontends can get updates in real-time from it without having to directly query it.

There are different ways to set this up, but some developers have wondered if it was possible to watch the whole Firestore collection at once. Here’s how to watch a whole variety of Firestore collections.

How to Watch an Entire Firestore Collection?


Usually, in Firestore, you will use the .onSnapshot() method to watch for changes to a specific document. When you use the .where() and .onSnapshot() methods inline, you can watch more than one document at once.

But for some projects, it makes sense for us to keep an eye on a whole collection for changes. This means that our real-time updates will happen every time a document is created, deleted, or changed.

Setting up something like this is easy. We’ll just use the .doc() or .where() method to add a snapshot trigger to the collection itself. In this case, the name of our collection is “triggers.”

db.collection("triggers").onSnapshot(() => { //DO SOMETHING HERE })

All done! With that small piece of code, Firebase will watch the whole Firestore collection in real-time and run your code whenever something changes.

 

Word of Caution


Now that you know how to watch a whole Firestore collection, we need to warn you about something. Keep an eye on your Firebase read quotas.

If the number of transactions in your collection starts to go up, apps that are keeping an eye on your whole collection will start to use a lot of reads.

Make sure you know about the possible consumption problems, especially if you are using the pay-as-you-go Blaze plan for Firebase.

Depending on your project, it might be a good idea to split up your high-throughput collections so that the costs of real-time monitoring aren’t too high. Happy Coding!

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