This document covers the basics of reading and writing Firebase data.
Firebase data is written to a FirebaseDatabase
reference and retrieved by
attaching an asynchronous listener to the reference. The listener is triggered
once for the initial state of the data and again anytime the data changes.
(Optional) Prototype and test with Firebase Local 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 Local 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 Local 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).
Using the Realtime Database emulator involves just a few steps:
- Adding a line of code to your app's test config to connect to the emulator.
- From the root of your local project directory, running
firebase emulators:start
. - 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 Local Emulator Suite introduction.
Get a DatabaseReference
To read or write data from the database, you need an instance of
DatabaseReference
:
Kotlin+KTX
private lateinit var database: DatabaseReference // ... database = Firebase.database.reference
Java
private DatabaseReference mDatabase; // ... mDatabase = FirebaseDatabase.getInstance().getReference();
Write data
Basic write operations
For basic write operations, you can use setValue()
to save data to a specified
reference, replacing any existing data at that path. You can use this method to:
- Pass types that correspond to the available JSON types as follows:
String
Long
Double
Boolean
Map<String, Object>
List<Object>
- Pass a custom Java object, if the class that defines it has a default constructor that takes no arguments and has public getters for the properties to be assigned.
If you use a Java object, the contents of your object are automatically mapped
to child locations in a nested fashion. Using a Java object also typically makes
your code more readable and easier to maintain. For example, if you have an
app with a basic user profile, your User
object might look as follows:
Kotlin+KTX
@IgnoreExtraProperties data class User(val username: String? = null, val email: String? = null) { // Null default values create a no-argument default constructor, which is needed // for deserialization from a DataSnapshot. }
Java
@IgnoreExtraProperties public class User { public String username; public String email; public User() { // Default constructor required for calls to DataSnapshot.getValue(User.class) } public User(String username, String email) { this.username = username; this.email = email; } }
You can add a user with setValue()
as follows:
Kotlin+KTX
fun writeNewUser(userId: String, name: String, email: String) { val user = User(name, email) database.child("users").child(userId).setValue(user) }
Java
public void writeNewUser(String userId, String name, String email) { User user = new User(name, email); mDatabase.child("users").child(userId).setValue(user); }
Using setValue()
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:
Kotlin+KTX
database.child("users").child(userId).child("username").setValue(name)
Java
mDatabase.child("users").child(userId).child("username").setValue(name);
Read data
Read data with persistent listeners
To read data at a path and listen for changes, use the addValueEventListener()
method to add a ValueEventListener
to a DatabaseReference
.
Listener | Event callback | Typical usage |
---|---|---|
ValueEventListener |
onDataChange() |
Read and listen for changes to the entire contents of a path. |
You can use the onDataChange()
method to read a static snapshot of the
contents at a given path, as they existed at the time of the event. This method
is triggered once when the listener is attached and again every time the data,
including children, changes. The event callback is passed a snapshot containing
all data at that location, including child data. If there is no data, the
snapshot will return false
when you call exists()
and null
when you call
getValue()
on it.
The following example demonstrates a social blogging application retrieving the details of a post from the database:
Kotlin+KTX
val postListener = object : ValueEventListener { override fun onDataChange(dataSnapshot: DataSnapshot) { // Get Post object and use the values to update the UI val post = dataSnapshot.getValue<Post>() // ... } override fun onCancelled(databaseError: DatabaseError) { // Getting Post failed, log a message Log.w(TAG, "loadPost:onCancelled", databaseError.toException()) } } postReference.addValueEventListener(postListener)
Java
ValueEventListener postListener = new ValueEventListener() { @Override public void onDataChange(DataSnapshot dataSnapshot) { // Get Post object and use the values to update the UI Post post = dataSnapshot.getValue(Post.class); // .. } @Override public void onCancelled(DatabaseError databaseError) { // Getting Post failed, log a message Log.w(TAG, "loadPost:onCancelled", databaseError.toException()); } }; mPostReference.addValueEventListener(postListener);
The listener receives a DataSnapshot
that contains the data at the specified
location in the database at the time of the event. Calling getValue()
on a
snapshot returns the Java object representation of the data. If no data exists
at the location, calling getValue()
returns null
.
In this example, ValueEventListener
also defines the onCancelled()
method that
is called if the read is canceled. For example, a read can be canceled if the
client doesn't have permission to read from a Firebase database location. This
method is passed a DatabaseError
object indicating why the failure occurred.
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 ValueEventListener
techniques described above
to read data to get notified of updates to the data from the backend. The
listener 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.
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.
Kotlin+KTX
mDatabase.child("users").child(userId).get().addOnSuccessListener {
Log.i("firebase", "Got value ${it.value}")
}.addOnFailureListener{
Log.e("firebase", "Error getting data", it)
}
Java
mDatabase.child("users").child(userId).get().addOnCompleteListener(new OnCompleteListener<DataSnapshot>() {
@Override
public void onComplete(@NonNull Task<DataSnapshot> task) {
if (!task.isSuccessful()) {
Log.e("firebase", "Error getting data", task.getException());
}
else {
Log.d("firebase", String.valueOf(task.getResult().getValue()));
}
}
});
Read once using a listener
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 addListenerForSingleValueEvent
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.
Updating or deleting data
Update specific fields
To simultaneously write to specific children of a node without overwriting other
child nodes, use the updateChildren()
method.
When calling updateChildren()
, 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 have a Post
class like this:
Kotlin+KTX
@IgnoreExtraProperties data class Post( var uid: String? = "", var author: String? = "", var title: String? = "", var body: String? = "", var starCount: Int = 0, var stars: MutableMap<String, Boolean> = HashMap(), ) { @Exclude fun toMap(): Map<String, Any?> { return mapOf( "uid" to uid, "author" to author, "title" to title, "body" to body, "starCount" to starCount, "stars" to stars, ) } }
Java
@IgnoreExtraProperties public class Post { public String uid; public String author; public String title; public String body; public int starCount = 0; public Map<String, Boolean> stars = new HashMap<>(); public Post() { // Default constructor required for calls to DataSnapshot.getValue(Post.class) } public Post(String uid, String author, String title, String body) { this.uid = uid; this.author = author; this.title = title; this.body = body; } @Exclude public Map<String, Object> toMap() { HashMap<String, Object> result = new HashMap<>(); result.put("uid", uid); result.put("author", author); result.put("title", title); result.put("body", body); result.put("starCount", starCount); result.put("stars", stars); return result; } }
To create a post and simultaneously update it to the recent activity feed and the posting user's activity feed, the blogging application uses code like this:
Kotlin+KTX
private fun writeNewPost(userId: String, username: String, title: String, body: String) { // Create new post at /user-posts/$userid/$postid and at // /posts/$postid simultaneously val key = database.child("posts").push().key if (key == null) { Log.w(TAG, "Couldn't get push key for posts") return } val post = Post(userId, username, title, body) val postValues = post.toMap() val childUpdates = hashMapOf<String, Any>( "/posts/$key" to postValues, "/user-posts/$userId/$key" to postValues, ) database.updateChildren(childUpdates) }
Java
private void writeNewPost(String userId, String username, String title, String body) { // Create new post at /user-posts/$userid/$postid and at // /posts/$postid simultaneously String key = mDatabase.child("posts").push().getKey(); Post post = new Post(userId, username, title, body); Map<String, Object> postValues = post.toMap(); Map<String, Object> childUpdates = new HashMap<>(); childUpdates.put("/posts/" + key, postValues); childUpdates.put("/user-posts/" + userId + "/" + key, postValues); mDatabase.updateChildren(childUpdates); }
This example uses push()
to create a post in the node containing posts for
all users at /posts/$postid
and simultaneously retrieve the key with
getKey()
. The key can then be used to create a second entry in the user's
posts at /user-posts/$userid/$postid
.
Using these paths, you can perform simultaneous updates to multiple locations in
the JSON tree with a single call to updateChildren()
, 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 add a
completion listener. Both setValue()
and updateChildren()
take an optional
completion listener that is called when the write has been successfully
committed to the database. If the call was unsuccessful, the listener is
passed an error object indicating why the failure occurred.
Kotlin+KTX
database.child("users").child(userId).setValue(user) .addOnSuccessListener { // Write was successful! // ... } .addOnFailureListener { // Write failed // ... }
Java
mDatabase.child("users").child(userId).setValue(user) .addOnSuccessListener(new OnSuccessListener<Void>() { @Override public void onSuccess(Void aVoid) { // Write was successful! // ... } }) .addOnFailureListener(new OnFailureListener() { @Override public void onFailure(@NonNull Exception e) { // Write failed // ... } });
Delete data
The simplest way to delete data is to call removeValue()
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 setValue()
or updateChildren()
. You can use this technique
with updateChildren()
to delete multiple children in a single API call.
Detach listeners
Callbacks are removed by calling the removeEventListener()
method on your
Firebase database reference.
If a listener has been added multiple times to a data location, it is called multiple times for each event, and you must detach it the same number of times to remove it completely.
Calling removeEventListener()
on a parent listener does not
automatically remove listeners registered on its child nodes;
removeEventListener()
must also be called on any child listeners
to remove the callback.
Save data as transactions
When working with data that could be corrupted by concurrent modifications, such as incremental counters, you can use a transaction operation. You give this operation two arguments: an update function and an optional completion callback. The update function 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:
Kotlin+KTX
private fun onStarClicked(postRef: DatabaseReference) { // ... postRef.runTransaction(object : Transaction.Handler { override fun doTransaction(mutableData: MutableData): Transaction.Result { val p = mutableData.getValue(Post::class.java) ?: return Transaction.success(mutableData) if (p.stars.containsKey(uid)) { // Unstar the post and remove self from stars p.starCount = p.starCount - 1 p.stars.remove(uid) } else { // Star the post and add self to stars p.starCount = p.starCount + 1 p.stars[uid] = true } // Set value and report transaction success mutableData.value = p return Transaction.success(mutableData) } override fun onComplete( databaseError: DatabaseError?, committed: Boolean, currentData: DataSnapshot?, ) { // Transaction completed Log.d(TAG, "postTransaction:onComplete:" + databaseError!!) } }) }
Java
private void onStarClicked(DatabaseReference postRef) { postRef.runTransaction(new Transaction.Handler() { @NonNull @Override public Transaction.Result doTransaction(@NonNull MutableData mutableData) { Post p = mutableData.getValue(Post.class); if (p == null) { return Transaction.success(mutableData); } if (p.stars.containsKey(getUid())) { // Unstar the post and remove self from stars p.starCount = p.starCount - 1; p.stars.remove(getUid()); } else { // Star the post and add self to stars p.starCount = p.starCount + 1; p.stars.put(getUid(), true); } // Set value and report transaction success mutableData.setValue(p); return Transaction.success(mutableData); } @Override public void onComplete(DatabaseError databaseError, boolean committed, DataSnapshot currentData) { // Transaction completed Log.d(TAG, "postTransaction:onComplete:" + databaseError); } }); }
Using a transaction prevents star counts from being incorrect if multiple users star the same post at the same time or the client had stale data. If the transaction is rejected, the server returns the current value to the client, which runs the transaction again with the updated value. This repeats until the transaction is accepted or too many attempts have been made.
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.
Kotlin+KTX
private fun onStarClicked(uid: String, key: String) { val updates: MutableMap<String, Any> = hashMapOf( "posts/$key/stars/$uid" to true, "posts/$key/starCount" to ServerValue.increment(1), "user-posts/$uid/$key/stars/$uid" to true, "user-posts/$uid/$key/starCount" to ServerValue.increment(1), ) database.updateChildren(updates) }
Java
private void onStarClicked(String uid, String key) { Map<String, Object> updates = new HashMap<>(); updates.put("posts/"+key+"/stars/"+uid, true); updates.put("posts/"+key+"/starCount", ServerValue.increment(1)); updates.put("user-posts/"+uid+"/"+key+"/stars/"+uid, true); updates.put("user-posts/"+uid+"/"+key+"/starCount", ServerValue.increment(1)); mDatabase.updateChildren(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 data on which listeners are being used or which is flagged to be kept in sync with the server. When data is read or written, this local version of the data is used 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 interaction with 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
- Working with lists of data
- Learn how to structure data
- Learn more about online and offline capabilities