How to build a CRUD app on Google Cloud Firestore

Google Cloud Firestore is a serverless document database with real-time sync and offline support, popular for web and mobile apps. Data lives in collections of documents; documents can hold subcollections. Firestore charges per read, write, and delete, so query design matters.

Prerequisites

• A Firebase or Google Cloud project with Firestore enabled.
• Node.js and the firebase SDK installed.

Steps

1. Enable Firestore

In the Firebase console, create a Firestore database in production mode and choose a region close to your users.

2. Model collections

A tasks collection where each document is a task works well. Keep documents small and avoid deeply nested data you will not query.

3. Add documents

import { getFirestore, collection, addDoc } from "firebase/firestore";
const db = getFirestore();
const ref = await addDoc(collection(db, "tasks"), { title: "write tutorial", done: false });

addDoc generates an ID; use setDoc to control the ID yourself.

4. Read documents

import { getDoc, doc } from "firebase/firestore";
const snap = await getDoc(doc(db, "tasks", ref.id));
console.log(snap.data());

5. Update and delete

import { updateDoc, deleteDoc } from "firebase/firestore";
await updateDoc(doc(db, "tasks", ref.id), { done: true });
await deleteDoc(doc(db, "tasks", ref.id));

6. Query and index

import { query, where, getDocs } from "firebase/firestore";
const q = query(collection(db, "tasks"), where("done", "==", false));
const results = await getDocs(q);

Compound queries (multiple filters or filter plus order) need a composite index; Firestore prints a link to create it on first run.

Verification

Watch documents appear and change in the Firestore Data viewer in the console. Add a real-time listener with onSnapshot and confirm updates push to the client without a refresh.

Next Steps

Write security rules so clients can only access their own data, batch writes for atomicity, and paginate large collections with startAfter cursors.