Skip to content


Couchbase Lite concepts — Data model — Documents


Document Structure

In Couchbase Lite the term 'document' refers to an entry in the database. You can compare it to a record, or a row in a table.

Each document has an ID or unique identifier. This ID is similar to a primary key in other databases.

You can specify the ID programmatically. If you omit it, it will be automatically generated as a UUID.


Couchbase documents are assigned to a Collection. The ID of a document must be unique within the Collection it is written to. You cannot change it after you have written the document.

The document also has a value which contains the actual application data. This value is stored as a dictionary of key-value (k-v) pairs. The values can be made of up several different Data Types such as numbers, strings, arrays, and nested objects.

Data Encoding

The document body is stored in an internal, efficient, binary form called Fleece. This internal form can be easily converted into a manageable native dictionary format for manipulation in applications.

Fleece data is stored in the smallest format that will hold the value whilst maintaining the integrity of the value.

Data Types

The Document class offers a set of property accessors for various scalar types, such as:

  • Boolean
  • Date
  • Double
  • Float
  • Int
  • Long
  • String

These accessors take care of converting to/from JSON encoding, and make sure you get the type you expect.

In addition to these basic data types Couchbase Lite provides for the following:

  • Dictionary represents a read-only key-value pair collection
  • MutableDictionary represents a writeable key-value pair collection
  • Array represents a readonly ordered collection of objects
  • MutableArray represents a writeable collection of objects
  • Blob represents an arbitrary piece of binary data


Couchbase Lite also provides for the direct handling of JSON data implemented in most cases by the provision of a toJSON() method on appropriate API classes (for example, on MutableDocument, Dictionary, Blob, and Array) — see Working with JSON Data.

Constructing a Document

An individual document often represents a single instance of an object in application code.

You can consider a document as the equivalent of a 'row' in a relational table, with each of the document’s attributes being equivalent to a 'column'.

Documents can contain nested structures. This allows developers to express many-to-many relationships without requiring a reference or join table, and is naturally expressive of hierarchical data.

Most apps will work with one or more documents, persisting them to a local database and optionally syncing them, either centrally or to the cloud.

In this section we provide an example of how you might create a hotel document, which provides basic contact details and price data.

Data Model
hotel: {
  type: string (value = `hotel`)
  name: string
  address: dictionary {
    street: string
    city: string
    state: string
    country: string
    code: string
  phones: array
  rate: float

Open a Database

First open your database. If the database does not already exist, Couchbase Lite will create it for you.

Couchbase documents are assigned to a Collection. All the CRUD examples in this document operate on a collection object.

// Get the database (and create it if it doesn’t exist).
val config = DatabaseConfiguration() = "path/to/db"
val database = Database("getting-started", config)
val collection = database.getCollection("myCollection")
    ?: throw IllegalStateException("collection not found")

See Databases for more information

Create a Document

Now create a new document to hold your application’s data.

Use the mutable form, so that you can add data to the document.

// Create your new document
val mutableDoc = MutableDocument()

For more on using Documents, see Document Initializers and Mutability.

Create a Dictionary

Now create a mutable dictionary (address).

Each element of the dictionary value will be directly accessible via its own key.

// Create and populate mutable dictionary
// Create a new mutable dictionary and populate some keys/values
val address = MutableDictionary()
address.setString("street", "1 Main st.")
address.setString("city", "San Francisco")
address.setString("state", "CA")
address.setString("country", "USA")
address.setString("code", "90210")


The Kotbase KTX extensions provide an idiomatic MutableDictionary creation function:

val address = mutableDictOf(
    "street" to "1 Main st.",
    "city" to "San Francisco",
    "state" to "CA",
    "country" to "USA",
    "code" to "90210"

Learn more about Using Dictionaries.

Create an Array

Since the hotel may have multiple contact numbers, provide a field (phones) as a mutable array.

// Create and populate mutable array
val phones = MutableArray()


The Kotbase KTX extensions provide an idiomatic MutableArray creation function:

val phones = mutableArrayOf(

Learn more about Using Arrays.

Populate a Document

Now add your data to the mutable document created earlier. Each data item is stored as a key-value pair.

// Initialize and populate the document

// Add document type to document properties 
mutableDoc.setString("type", "hotel")

// Add hotel name string to document properties 
mutableDoc.setString("name", "Hotel Java Mo")

// Add float to document properties 
mutableDoc.setFloat("room_rate", 121.75f)

// Add dictionary to document's properties 
mutableDoc.setDictionary("address", address)

// Add array to document's properties 
mutableDoc.setArray("phones", phones)


Couchbase recommends using a type attribute to define each logical document type.

Save a Document

Now persist the populated document to your Couchbase Lite database. This will auto-generate the document id.

// Save the document changes

Close the Database

With your document saved, you can now close our Couchbase Lite database.

// Close the database 

Working with Data

Checking a Document’s Properties

To check whether a given property exists in the document, use the Document.contains(key: String) method.

If you try to access a property which doesn’t exist in the document, the call will return the default value for that getter method (0 for Document.getInt(), 0.0 for Document.getFloat(), etc.).

Date accessors

Couchbase Lite offers Date accessors as a convenience. Dates are a common data type, but JSON doesn’t natively support them, so the convention is to store them as strings in ISO-8601 format.

Example 1. Date Getter

This example sets the date on the createdAt property and reads it back using the Document.getDate() accessor method.

val date = doc.getDate("createdAt")

Using Dictionaries

API References

Example 2. Read Only

// NOTE: No error handling, for brevity (see getting started)
val document = collection.getDocument("doc1")

// Getting a dictionary from the document's properties
val dict = document?.getDictionary("address")

// Access a value with a key from the dictionary
val street = dict?.getString("street")

// Iterate dictionary
dict?.forEach { key ->
    println("Key $key = ${dict.getValue(key)}")

// Create a mutable copy
val mutableDict = dict?.toMutable()

Example 3. Mutable

// NOTE: No error handling, for brevity (see getting started)

// Create a new mutable dictionary and populate some keys/values
val mutableDict = MutableDictionary()
mutableDict.setString("street", "1 Main st.")
mutableDict.setString("city", "San Francisco")

// Add the dictionary to a document's properties and save the document
val mutableDoc = MutableDocument("doc1")
mutableDoc.setDictionary("address", mutableDict)

Using Arrays

API References

Example 4. Read Only

// NOTE: No error handling, for brevity (see getting started)

val document = collection.getDocument("doc1")

// Getting a phones array from the document's properties
val array = document?.getArray("phones")

// Get element count
val count = array?.count

// Access an array element by index
val phone = array?.getString(1)

// Iterate array
array?.forEachIndexed { index, item ->
    println("Row $index = $item")

// Create a mutable copy
val mutableArray = array?.toMutable()

Example 5. Mutable

// NOTE: No error handling, for brevity (see getting started)

// Create a new mutable array and populate data into the array
val mutableArray = MutableArray()

// Set the array to document's properties and save the document
val mutableDoc = MutableDocument("doc1")
mutableDoc.setArray("phones", mutableArray)

Using Blobs

For more on working with blobs, see Blobs.

Document Initializers

You can use the following methods/initializers:

  • Use the MutableDocument() initializer to create a new document where the document ID is randomly generated by the database.
  • Use the MutableDocument(id: String?) initializer to create a new document with a specific ID.
  • Use the Collection.getDocument() method to get a document. If the document doesn’t exist in the collection, the method will return null. You can use this behavior to check if a document with a given ID already exists in the collection.

Example 6. Persist a document

val doc = MutableDocument()
doc.apply {
    setString("type", "task")
    setString("owner", "todo")


The Kotbase KTX extensions provide a document builder DSL:

val doc = MutableDocument {
    "type" to "task"
    "owner" to "todo"
    "createdAt" to


By default, a document is immutable when it is read from the database. Use Document.toMutable() to create an updatable instance of the document.

Example 7. Make a mutable document

Changes to the document are persisted to the database when the save method is called.

collection.getDocument("xyz")?.toMutable()?.let {
    it.setString("name", "apples")


Any user change to the value of reserved keys (_id, _rev, or _deleted) will be detected when a document is saved and will result in an exception (Error Code 5 — CorruptRevisionData) — see also Document Constraints.

Batch operations

If you’re making multiple changes to a database at once, it’s faster to group them together. The following example persists a few documents in batch.

Example 8. Batch operations

database.inBatch {
    for (i in 0..9) {
        val doc = MutableDocument()
        doc.apply {
            setValue("type", "user")
            setValue("name", "user $i")
            setBoolean("admin", false)
        println("saved user document: ${doc.getString("name")}")

At the local level this operation is still transactional: no other Database instances, including ones managed by the replicator, can make changes during the execution of the block, and other instances will not see partial changes. But Couchbase Mobile is a distributed system, and due to the way replication works, there’s no guarantee that Sync Gateway or other devices will receive your changes all at once.

Document change events

You can register for document changes. The following example registers for changes to the document with ID user.john and prints the verified_account property when a change is detected.

Example 9. Document change events

collection.addDocumentChangeListener("user.john") { change ->
    collection.getDocument(change.documentID)?.let {
        println("Status: ${it.getString("verified_account")}")

Using Kotlin Flows

Kotlin users can also take advantage of Flows to monitor for changes.

The following methods show how to watch for document changes in a given collection or for changes to a specific document.

val collChanges: Flow<List<String>> = collection.collectionChangeFlow()
    .map { it.documentIDs }
val docChanges: Flow<DocumentChange> = collection.documentChangeFlow("1001")
    .mapNotNull { change ->
        change.takeUnless {

Document Expiration

Document expiration allows users to set the expiration date for a document. When the document expires, it is purged from the database. The purge is not replicated to Sync Gateway.

Example 10. Set document expiration

This example sets the TTL for a document to 1 day from the current time.

// Purge the document one day from now
    "doc123", + 1.days

// Reset expiration
collection.setDocumentExpiration("doc1", null)

// Query documents that will be expired in less than five minutes
val query = QueryBuilder
            Expression.longValue(( + 5.minutes).toEpochMilliseconds())

Document Constraints

Couchbase Lite APIs do not explicitly disallow the use of attributes with the underscore prefix at the top level of document. This is to facilitate the creation of documents for use either in local only mode where documents are not synced, or when used exclusively in peer-to-peer sync.


"_id", :"_rev" and "_sequence" are reserved keywords and must not be used as top-level attributes — see Example 11.

Users are cautioned that any attempt to sync such documents to Sync Gateway will result in an error. To be future-proof, you are advised to avoid creating such documents. Use of these attributes for user-level data may result in undefined system behavior.

For more guidance — see Sync Gateway - data modeling guidelines

Example 11. Reserved Keys List

  • _attachments
  • _deleted 1
  • _id 1
  • _removed
  • _rev 1
  • _sequence

Working with JSON Data

In this section
Arrays | Blobs | Dictionaries | Documents | Query Results as JSON

The toJSON() typed-accessor means you can easily work with JSON data, native and Couchbase Lite objects.


Convert an Array to and from JSON using the toJSON() and toList() methods — see Example 12.

Additionally, you can:

Example 12. Arrays as JSON strings

// JSON String -- an Array (3 elements. including embedded arrays)
val jsonString = """[{"id":"1000","type":"hotel","name":"Hotel Ted","city":"Paris","country":"France","description":"Undefined description for Hotel Ted"},{"id":"1001","type":"hotel","name":"Hotel Fred","city":"London","country":"England","description":"Undefined description for Hotel Fred"},{"id":"1002","type":"hotel","name":"Hotel Ned","city":"Balmain","country":"Australia","description":"Undefined description for Hotel Ned","features":["Cable TV","Toaster","Microwave"]}]"""

// initialize array from JSON string
val mArray = MutableArray(jsonString)

// Create and save new document using the array
for (i in 0 ..< mArray.count) {
    mArray.getDictionary(i)?.apply {
        println(getString("name") ?: "unknown")"id"), toMap()))

// Get an array from the document as a JSON string
collection.getDocument("1002")?.getArray("features")?.apply {
    // Print its elements
    for (feature in toList()) {


Convert a Blob to JSON using the toJSON() method — see Example 13.

You can use isBlob() to check whether a given dictionary object is a blob or not — see Example 13.

Note that the blob object must first be saved to the database (generating the required metadata) before you can use the toJSON() method.

Example 13. Blobs as JSON strings

val thisBlob = collection.getDocument("thisdoc-id")!!.toMap()
if (!Blob.isBlob(thisBlob)) {
val blobType = thisBlob["content_type"].toString()
val blobLength = thisBlob["length"] as Number?

See also: Blobs


Convert a Dictionary to and from JSON using the toJSON() and toMap() methods — see Example 14.

Additionally, you can:

Example 14. Dictionaries as JSON strings

val jsonString = """{"id":"1002","type":"hotel","name":"Hotel Ned","city":"Balmain","country":"Australia","description":"Undefined description for Hotel Ned","features":["Cable TV","Toaster","Microwave"]}"""

val mDict = MutableDictionary(jsonString)
println("Details for: ${mDict.getString("name")}")
mDict.forEach { key ->
    println(key + " => " + mDict.getValue(key))


Convert a Document to and from JSON strings using the toJSON() and toMap() methods — see Example 15.

Additionally, you can:

Example 15. Documents as JSON strings

    .forEach {
        it.getString("metaId")?.let { thisId ->
            srcColl.getDocument(thisId)?.toJSON()?.let { json ->
                println("JSON String = $json")
                val hotelFromJSON = MutableDocument(thisId, json)
                dstColl.getDocument(thisId)?.toMap()?.forEach { e ->
                    println("${e.key} => ${e.value}")

Query Results as JSON

Convert a query Result to a JSON string using its toJSON() accessor method. The JSON string can easily be serialized or used as required in your application. See Example 16 for a working example using kotlinx-serialization.

Example 16. Using JSON Results

// Uses kotlinx-serialization JSON processor
data class Hotel(val id: String, val type: String, val name: String)

val hotels = mutableListOf<Hotel>()

val query = QueryBuilder

query.execute().use { rs ->
    rs.forEach {

        // Get result as JSON string
        val json = it.toJSON()

        // Get JsonObject map from JSON string
        val mapFromJsonString = Json.decodeFromString<JsonObject>(json)

        // Use created JsonObject map
        val hotelId = mapFromJsonString["id"].toString()
        val hotelType = mapFromJsonString["type"].toString()
        val hotelName = mapFromJsonString["name"].toString()

        // Get custom object from JSON string
        val hotel = Json.decodeFromString<Hotel>(json)

JSON String Format

If your query selects ALL then the JSON format will be:

  database-name: {
    key1: "value1",
    keyx: "valuex"

If your query selects a sub-set of available properties then the JSON format will be:

  key1: "value1",
  keyx: "valuex"

  1. Any change to this reserved key will be detected when it is saved and will result in a Couchbase exception (Error Code 5 — CorruptRevisionData