The Ioto agent database (DB) supports optional transparent synchronization of data to and from the cloud.
Ioto data synchronization takes the pain out of sending device data to the cloud. It automatically and transparently synchronizes data between your devices and the cloud.
The database synchronization is full-duplex, i.e. data can be modified in the device or in the cloud and it will be replicated to the other side. The synchronization is controllable on a per-model basis.
Database Replication Features
- Transparent replication.
- Bi-directional synchronization to and from the cloud.
- Per-table synchronization control.
- Resilient catch-up should the device or cloud go offline.
- Database triggers for notification when changes arrive.
The Ioto Database Synchronization service dramatically eases the task of centralizing the data management of a pool of devices. Each device can store data locally and it will be transparently, efficiently and automatically replicated to the cloud. Once in the cloud, it can be easily interrogated and queried for analytics, operational control and intelligence.
Each side has fast, predictable local access to the data. Coupled with reliable replication semantics you can work locally while Ioto takes care of the replication.
How It Works
To replicate cloud-side data, the Ioto service uses AWS DynamoDB streams to capture modifications made to the table data. The stream is connected to an Ioto service Lambda running that transports the updates via MQTT messages to a special topic that is only known to the specific device.
The Ioto device agent subscribes to this topic and receives MQTT messages containing the changed data. The agent then applies those changes to the local database.
In reverse, the Ioto agent registers a database trigger that is called whenever local changes are made to the device's database. When the trigger is invoked, the agent sends an MQTT message with the changes to the Ioto service that updates the cloud database.
Ioto keeps track of the last update sent and received and will retransmit lost updates.
When a device is rebooted after being offline, it sends a "sync" message to the Ioto service to retrieve all changes made to the cloud database since the last change notification was received from the cloud. In this way, changes made while the device is offline are not lost.
Ioto can synchronize changes to the cloud on a per model basis. The schema process property defines how to synchronize each model. You can "enable" a model to be stored in the cloud, in the device or in both places. You can also control the replication direction flow of changes.
For each Model in the schema, a property under process specifies where the model resides and how it should be synchronized.
In this example: The Status model is only enabled (exists) in the cloud. The Fault model exists in both the cloud and on the device and synchronization occurs only from the device "up" to the cloud.
A model's enable property can be set to "cloud", "device" or "both" to define where the model can exist. The default is "both".
A model's sync property can be set to "up", "down", "both" or "none" to define the directional flow of replication updates. A value of "up" means replicate changes from the device "up" to the cloud. A value of "down" means replicate changes only from the cloud "down" to the device. The default is "none".
Replication Best Practices
Synchronization of model items is done on a per-item basis and not field by field. This means that a change of one field by the cloud can overwrite a change of another field on the device. For this reason, it is best to have the sync direction be either "up" or "down".
You should only select "both" as your sync direction for models that can be updated by both cloud and device at the same time without loss of data or conflict.
To optimize network traffic, database changes will be sent up to the cloud in batches. These are controlled by the database.syncDelay and the database.syncLimit properties. The syncDelay is a delay before sending change batches to the cloud. The syncLimit is a size limit of the change set before sending a change batch. These are set to 5 seconds and 10K by default.
You can force a sync save at any point by calling ioSync.