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TQLEngine stores the following variables/data of each model instance: Jira LegacyshowSummaryfalseserverJIRA (mqidentity.atlassian.net)serverId77fb3325-4051-36d9-bcc7-761f62050707keyDOCS-58There are three types of Models that can be defined at the time of creating models for your IoT applications. The three models are:

• DataModel
• ThingModel
• AppModel
  
  

Model lifecycle consists of three steps

• Definition - Models are defined either using TQLStudio Model Editor or any IDE of your choice. 
  Modeling Language (Thing Definition Language) is essential to define models.
• Deploy - As part of a deployable unit within TQLEngine's package file. Models definitions are made part of SffTqlFacet Facet type.
• Query - Querying of model consists of CRUD as well as Subscription (and notification).

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Model Instances

Once models are defined and deployed their schematic layout is persisted in Storage (TQL Cache) defined at the time of the deployment. Note that

even though models are persisted in SQL type of storage that data is highly unstructured and stored in proprietary format.

Before Models can be queried using Find - Models must be initialized or populated with data. The result of model creation is called Model Instances.

For example:

Attribute values (Value)

Attribute known values (Known)

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