Read and Write Data

(Optional) Prototype and test with Firebase Emulator Suite

Before talking about how your app reads from and writes to Realtime Database, let's introduce a set of tools you can use to prototype and test Realtime Database functionality: Firebase Emulator Suite. If you're trying out different data models, optimizing your security rules, or working to find the most cost-effective way to interact with the back-end, being able to work locally without deploying live services can be a great idea.

A Realtime Database emulator is part of the Emulator Suite, which enables your app to interact with your emulated database content and config, as well as optionally your emulated project resources (functions, other databases, and security rules).emulator_suite_short

Using the Realtime Database emulator involves just a few steps:

  1. Adding a line of code to your app's test config to connect to the emulator.
  2. From the root of your local project directory, running firebase emulators:start.
  3. Making calls from your app's prototype code using a Realtime Database platform SDK as usual, or using the Realtime Database REST API.

A detailed walkthrough involving Realtime Database and Cloud Functions is available. You should also have a look at the Emulator Suite introduction.

Get a DatabaseReference

To read or write data from the database, you need an instance of DatabaseReference:

DatabaseReference ref = FirebaseDatabase.instance.ref();

Write data

This document covers the basics of reading and writing Firebase data.

Firebase data is written to a DatabaseReference and retrieved by awaiting or listening for events emitted by the reference. Events are emitted once for the initial state of the data and again anytime the data changes.

Basic write operations

For basic write operations, you can use set() to save data to a specified reference, replacing any existing data at that path. You can set a reference to the following types: String, boolean, int, double, Map, List.

For instance, you can add a user with set() as follows:

DatabaseReference ref = FirebaseDatabase.instance.ref("users/123");

await ref.set({
  "name": "John",
  "age": 18,
  "address": {
    "line1": "100 Mountain View"

Using set() in this way overwrites data at the specified location, including any child nodes. However, you can still update a child without rewriting the entire object. If you want to allow users to update their profiles you could update the username as follows:

DatabaseReference ref = FirebaseDatabase.instance.ref("users/123");

// Only update the name, leave the age and address!
await ref.update({
  "age": 19,

The update() method accepts a sub-path to nodes, allowing you to update multiple nodes on the database at once:

DatabaseReference ref = FirebaseDatabase.instance.ref("users");

await ref.update({
  "123/age": 19,
  "123/address/line1": "1 Mountain View",

Read data

Read data by listening for value events

To read data at a path and listen for changes, use the onValue property of DatabaseReference to listen for DatabaseEvents.

You can use the DatabaseEvent to read the data at a given path, as it exists at the time of the event. This event is triggered once when the listener is attached and again every time the data, including any children, changes. The event has a snapshot property containing all data at that location, including child data. If there is no data, the snapshot's exists property will be false and its value property will be null.

The following example demonstrates a social blogging application retrieving the details of a post from the database:

DatabaseReference starCountRef =
starCountRef.onValue.listen((DatabaseEvent event) {
    final data = event.snapshot.value;

The listener receives a DataSnapshot that contains the data at the specified location in the database at the time of the event in its value property.

Read data once

Read once using get()

The SDK is designed to manage interactions with database servers whether your app is online or offline.

Generally, you should use the value events techniques described above to read data to get notified of updates to the data from the backend. Those techniques reduce your usage and billing, and are optimized to give your users the best experience as they go online and offline.

If you need the data only once, you can use get() to get a snapshot of the data from the database. If for any reason get() is unable to return the server value, the client will probe the local storage cache and return an error if the value is still not found.

The following example demonstrates retrieving a user's public-facing username a single time from the database:

final ref = FirebaseDatabase.instance.ref();
final snapshot = await ref.child('users/$userId').get();
if (snapshot.exists) {
} else {
    print('No data available.');

Unnecessary use of get() can increase use of bandwidth and lead to loss of performance, which can be prevented by using a realtime listener as shown above.

Read data once with once()

In some cases you may want the value from the local cache to be returned immediately, instead of checking for an updated value on the server. In those cases you can use once() to get the data from the local disk cache immediately.

This is useful for data that only needs to be loaded once and isn't expected to change frequently or require active listening. For instance, the blogging app in the previous examples uses this method to load a user's profile when they begin authoring a new post:

final event = await ref.once(DatabaseEventType.value);
final username = event.snapshot.value?.username ?? 'Anonymous';

Updating or deleting data

Update specific fields

To simultaneously write to specific children of a node without overwriting other child nodes, use the update() method.

When calling update(), you can update lower-level child values by specifying a path for the key. If data is stored in multiple locations to scale better, you can update all instances of that data using data fan-out. For example, a social blogging app might want to create a post and simultaneously update it to the recent activity feed and the posting user's activity feed. To do this, the blogging application uses code like this:

void writeNewPost(String uid, String username, String picture, String title,
        String body) async {
    // A post entry.
    final postData = {
        'author': username,
        'uid': uid,
        'body': body,
        'title': title,
        'starCount': 0,
        'authorPic': picture,

    // Get a key for a new Post.
    final newPostKey =

    // Write the new post's data simultaneously in the posts list and the
    // user's post list.
    final Map<String, Map> updates = {};
    updates['/posts/$newPostKey'] = postData;
    updates['/user-posts/$uid/$newPostKey'] = postData;

    return FirebaseDatabase.instance.ref().update(updates);

This example uses push() to create a post in the node containing posts for all users at /posts/$postid and simultaneously retrieve the key with key. The key can then be used to create a second entry in the user's posts at /user-posts/$userid/$postid.

Using these paths, you can perform simultaneous updates to multiple locations in the JSON tree with a single call to update(), such as how this example creates the new post in both locations. Simultaneous updates made this way are atomic: either all updates succeed or all updates fail.

Add a completion callback

If you want to know when your data has been committed, you can register completion callbacks. Both set() and update() return Futures, to which you can attach success and error callbacks that are called when the write has been committed to the database and when the call was unsuccessful.

    .then((_) {
        // Data saved successfully!
    .catchError((error) {
        // The write failed...

Delete data

The simplest way to delete data is to call remove() on a reference to the location of that data.

You can also delete by specifying null as the value for another write operation such as set() or update(). You can use this technique with update() to delete multiple children in a single API call.

Save data as transactions

When working with data that could be corrupted by concurrent modifications, such as incremental counters, you can use a transaction by passing a transaction handler to runTransaction(). A transaction handler takes the current state of the data as an argument and returns the new desired state you would like to write. If another client writes to the location before your new value is successfully written, your update function is called again with the new current value, and the write is retried.

For instance, in the example social blogging app, you could allow users to star and unstar posts and keep track of how many stars a post has received as follows:

void toggleStar(String uid) async {
  DatabaseReference postRef =

  TransactionResult result = await postRef.runTransaction((Object? post) {
    // Ensure a post at the ref exists.
    if (post == null) {
      return Transaction.abort();

    Map<String, dynamic> _post = Map<String, dynamic>.from(post as Map);
    if (_post["stars"] is Map && _post["stars"][uid] != null) {
      _post["starCount"] = (_post["starCount"] ?? 1) - 1;
      _post["stars"][uid] = null;
    } else {
      _post["starCount"] = (_post["starCount"] ?? 0) + 1;
      if (!_post.containsKey("stars")) {
        _post["stars"] = {};
      _post["stars"][uid] = true;

    // Return the new data.
    return Transaction.success(_post);

By default, events are raised each time the transaction update function runs, so you run the function run multiple times, you may see intermediate states. You can set applyLocally to false to suppress these intermediate states and instead wait until the transaction has completed before events are raised:

await ref.runTransaction((Object? post) {
  // ...
}, applyLocally: false);

The result of a transaction is a TransactionResult, which contains information such as whether the transaction was committed, and the new snapshot:

DatabaseReference ref = FirebaseDatabase.instance.ref("posts/123");

TransactionResult result = await ref.runTransaction((Object? post) {
  // ...

print('Committed? ${result.committed}'); // true / false
print('Snapshot? ${result.snapshot}'); // DataSnapshot

Cancelling a transaction

If you want to safely cancel a transaction, call Transaction.abort() to throw an AbortTransactionException:

TransactionResult result = await ref.runTransaction((Object? user) {
  if (user !== null) {
    return Transaction.abort();

  // ...

print(result.committed); // false

Atomic server-side increments

In the above use case we're writing two values to the database: the ID of the user who stars/unstars the post, and the incremented star count. If we already know that user is starring the post, we can use an atomic increment operation instead of a transaction.

void addStar(uid, key) async {
  Map<String, Object?> updates = {};
  updates["posts/$key/stars/$uid"] = true;
  updates["posts/$key/starCount"] = ServerValue.increment(1);
  updates["user-posts/$key/stars/$uid"] = true;
  updates["user-posts/$key/starCount"] = ServerValue.increment(1);
  return FirebaseDatabase.instance.ref().update(updates);

This code does not use a transaction operation, so it does not automatically get re-run if there is a conflicting update. However, since the increment operation happens directly on the database server, there is no chance of a conflict.

If you want to detect and reject application-specific conflicts, such as a user starring a post that they already starred before, you should write custom security rules for that use case.

Work with data offline

If a client loses its network connection, your app will continue functioning correctly.

Every client connected to a Firebase database maintains its own internal version of any active data. When data is written, it's written to this local version first. The Firebase client then synchronizes that data with the remote database servers and with other clients on a "best-effort" basis.

As a result, all writes to the database trigger local events immediately, before any data is written to the server. This means your app remains responsive regardless of network latency or connectivity.

Once connectivity is reestablished, your app receives the appropriate set of events so that the client syncs with the current server state, without having to write any custom code.

We'll talk more about offline behavior in Learn more about online and offline capabilities.

Next steps