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Atlas Device SDK is a collection of tools to accelerate app development on a broad range of devices:
A built-in Sync client that can synchronize your data between devices and with a MongoDB Atlas backend.
An offline-first object database to persist data on device.
The ability to call Atlas Functions to do work in the cloud.
A client to query MongoDB data sources directly from your app.
The ability to access the MongoDB GraphQL API from the client.
You can use the SDK's object store, Realm, to read, write, and react to changes in your data on device. Add Device Sync, Atlas Functions, or the MongoDB Atlas client to take advantage of MongoDB Atlas features and access data sources from your app.
Mobile and edge developers face a number of unique challenges:
Handle the unpredictable environment of mobile and edge devices. Connections can be lost, devices can shut down at any time, and clients often update long after release.
Maintain common data schemas and APIs between clients, backend APIs, and databases.
Stay aware of security vulnerabilities across all components in an ecosystem.
Consistently serialize objects between networks, database storage, and application memory.
Program in the languages and frameworks for one or more operating systems.
All of these challenges present different obstacles. You can solve each in isolation with a wide variety of libraries and frameworks. Selecting the best solution for each problem with the right tradeoffs is a challenge mobile and edge developers know all too well.
The combination of multiple environments creates more challenges. For instance, you can use a Java library on your Android client to serialize objects, but that library won't work on iOS. And this doesn't take into account consistency across backend services.
The SDKs solve many common mobile and edge programming headaches:
Device storage: The SDKs run right on client devices. Access objects using the native query language for each platform. Storing, accessing, and updating your data is simple and lightweight.
Network reliability: The SDKs are offline-first. You always read from and write to the persistence layer on the device, not over the network. When Device Sync is enabled, the SDK synchronizes data with App Services over the network in a background thread. The sync protocol resolves conflicts consistently on each client and in the linked Atlas cluster.
Reactive UI: Live objects always reflect the latest data stored in the database. You can subscribe to changes, letting you keep your UI consistently up to date.
Client applications generate a lot of data. Whether it's uploaded reviews and ratings, posts and comments on a blog, or inventory in a kitchen, you need to store that data somewhere.
The SDKs use Atlas Device Sync to synchronize app data between clients and MongoDB Atlas. Atlas Device Sync handles network access and conflict resolution in a background thread of your application, so your application logic stays the same regardless of network conditions.
Once your client data is in Atlas, you can leverage the full Atlas developer data platform. Perform aggregations and other complex workloads with the full capabilities of MongoDB. Or connect your Atlas instance to Charts to visualize your data in real time. Storing your data in Atlas makes it easy to share data across users and platforms.
The SDKs integrate with App Services to easily and securely work with data from your app:
Query MongoDB Atlas directly from the SDKs using built-in MongoDB interfaces. You can also configure the Atlas Data API to query MongoDB using an HTTP client in your app.
App Services Users and Authentication provide built-in user management. Integrate with a JWT authentication service or directly with third-party authentication providers, like Facebook, Google, and Apple.
Atlas Triggers automatically execute an Atlas Function at a scheduled time or when an event occurs, such as a change to a MongoDB database in Atlas or a user logs in.
The Atlas GraphQL API accesses data stored in a linked MongoDB cluster with a standard GraphQL client.
App Services Rules control who accesses what data.
App Services Values and Secrets define global variables and private credentials once and use them across your entire App.
Use the SDKs instead of MongoDB Drivers if you want:
A cross-platform object store optimized for mobile and edge devices that can sync data automatically with MongoDB Atlas.
Built-in conflict resolution when syncing data across users and devices.
The ability to access data on a device regardless of network connectivity.
Reactive UIs driven by your data.
Built-in user management and authentication for client devices.
Support for complex user permissions and sync logic to determine what data clients can read and write.
Optimization for heavy insert-only workloads from mobile or edge devices.
The ability to execute Atlas Functions from the client.
Use MongoDB Drivers instead of the SDKs if:
You host MongoDB on your own infrastructure. The SDKs are either device-only or work with MongoDB Atlas.
You want to directly work with documents instead of objects, or you have your own mapping layer. The SDKs store data as objects on the device, and Device Sync maps them to MongoDB documents when it syncs with Atlas.
You already have a stack like MERN or MEAN and don't need the functionality provided by the SDKs.
The persistence layer that the SDKs use on the device is Realm. The SDKs wrap the Realm Core C++ database, and provide language-idiomatic APIs to work with files on the filesystem and perform read and write operations.
Realm is a reactive, object-oriented, cross-platform, mobile database:
Reactive: query the current state of data and subscribe to state changes like the result of a query, or even changes to a single object.
Object-oriented: organizes data as objects, rather than rows, documents, or columns.
Cross-platform: use the same database on iOS, Android, Linux, macOS, or Windows. Just define a schema for each SDK you use.
Mobile: designed for the low-power, battery-sensitive, real-time environment of a mobile device.
The Realm data model is similar to both relational and document databases but has distinct differences from both. Realm stores objects in files on the device, and an app may use multiple realm files to organize data and enforce access controls.
- A realm is not a single, application-wide database.
- Applications based on other database systems generally store all of their data in a single database. Apps often split data across multiple realms to organize data more efficiently and to enforce access controls.
- A realm is not a relational table.
- Normalized tables in relational databases only store one type of information, such as street addresses or items in a store inventory. A realm can contain any number of object types that are relevant to a given domain.
- A realm is not a collection of schemaless documents.
- Document databases don't necessarily enforce a strict schema for the data in each collection. While similar to documents in form, every Realm object conforms to a schema for a specific object type in the realm. An object cannot contain a property that is not described by its schema.
You can read back the data that you have stored in Realm by finding, filtering, and sorting objects. You can optionally section these results by a key path, making it easier to populate sectioned tables.
All Realm objects are live objects, which means they automatically update whenever they're modified. Realm emits a notification event whenever any property changes.
You can use live objects to work with object-oriented data natively without an ORM tool. Live objects are direct proxies to the underlying stored data, which means that a live object doesn't directly contain data. Instead, a live object always references the most up-to-date data on disk and lazy loads property values when you access them from a collection. This means that a realm can contain many objects but only pay the performance cost for data that the application is actually using.
Valid write operations on a live object automatically persist to the realm and propagate to any other synced clients. You do not need to call an update method, modify the realm, or otherwise "push" updates.
Realm is an entire database written from scratch in C++, instead of building on top of an underlying database engine like SQLite. Realm's underlying storage layer uses B+ trees to organize objects. As a result, Realm controls optimizations from the storage level all the way up to the access level.
Realm stores data in realms: collections of heterogeneous realm objects. You can think of each realm as a database. Each object in a realm is equivalent to a row in a SQL database table or a MongoDB document. Unlike SQL, realms do not separate different object types into individual tables.
Realm stores objects as groups of property values. We call this column-based storage. This means that queries or writes for individual objects can be slower than row-based storage equivalents when unindexed, but querying a single field across multiple objects or fetching multiple objects can be much faster due to spatial locality and in-CPU vector operations.
Realm uses a zero-copy design to make queries faster than an ORM, and often faster than raw SQLite.
Realm uses a technique called copy-on-write, which copies data to a new location on disk for every write operation instead of overwriting older data on disk. Once the new copy of data is fully written, the database updates existing references to that data. Older data is only garbage collected when it is no longer referenced or actively in use by a client application.
Because of copy-on-write, older copies of data remain valid, since all of the references in those copies still point to other valid data. Realm leverages this fact to offer multiple versions of data simultaneously to different threads in client applications. Most applications tie data refreshes to the repaint cycle of the looper thread that controls the UI, since data only needs to refresh as often as the UI does. Longer-running procedures on background threads, such as large write operations, can work with a single version of data for a longer period of time before committing their changes.
Writes use memory mapping to avoid copying data back and forth from memory to storage. Accessors and mutators read and write to disk via memory mapping. As a result, object data is never stored on the stack or heap of your app. By default, data is memory-mapped as read-only to prevent accidental writes.
Realm uses operating system level paging, trusting each operating system to implement memory mapping and persistence better than a single library could on its own.
Realm automatically reuses free space that is no longer needed after database writes. However, realm files never shrink automatically, even if the amount of data stored in your realm decreases significantly. Compact your realm to optimize storage space and decrease file size if possible.
You should compact your realms occasionally to keep them at an optimal size. You can do this manually, or by configuring your realms to compact on launch. However, Realm reclaims unused space for future writes, so compaction is only an optimization to conserve space on-device.