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Digital Twins

The physical asset and its data, kept in step.

A digital twin is a model that has to stay true: the asset structure is recorded once, and the telemetry has to keep it current.

See Digital Twins All of Infrastructure & Technology

A twin that is a query over operational data, not a synchronised copy.

The story

A twin that is a query over operational data, not a synchronised copy.

Where it starts

Asset model

Assets, components, hierarchy and their relationships. It is the first of 4 workloads running in Digital Twins.

The question it raises

No synchronised copy

The twin is read from the operational layer, which removes the job that keeps a copy in step.

Why one question is hard

From Model to Query

Digital Twins data moves through 4 stages — Model → Bind → Describe → Query. The shapes in play are Time series, Graph, SQL, JSON / documents, Vector, Objects, and answering one question means reading across all of them.

What PLOMID contributes

A twin is a model plus a feed. These are the parts that keep the feed attached to the model.

  • Relationships held as data Edges expressed directly remove the reconstruction that happens at query time when relationships live in a join.
  • Time-ordered storage Measurements and events are stored beside the records and documents they describe, so history and current state agree.
  • One data layer Rows, documents and time-ordered events live in one system, so a question is asked once instead of once per store.
The environment

Asset models, live telemetry, relationships and the queries run against them.

Twins combine structured asset records, relationship structure, time-ordered telemetry and documents describing them. Built as three systems, the twin drifts. PLOMID holds the model and the measurements in one layer, so the twin is a query over the operational data rather than a synchronised copy of it.

Workload architecture

The system reading itself.

Planning, execution and transactions first — then the workloads that use them and the shapes they name.

Digital Twins · workload architecture
Workloads

What runs against this data.

  • Asset model
  • Live state
  • Documents and specifications
  • Computed views
Data models

The shapes those workloads read and write.

  • Time series
  • Graph
  • SQL
  • JSON / documents
  • Vector
  • Objects
The layer

One path from a request to the data it names.

  • Planning Predicates narrow the work before it runs
  • Execution Records, fields and windows answered together
  • Transactions Readers and writers do not block each other
Surfaces

How the work reaches the layer.

  • SQL surface The query language the layer is documented in
  • Applications Services and jobs writing and reading as they run
  • Analytics & AI clients The same layer, the same access path
One environment · many workloads

What runs against digital twins data.

4 workload families over one set of shapes. Choose one to see what it moves and where it lands.

Assets, components, hierarchy and their relationships.

  • Planned once against the layer, not once per store
  • Read beside the records it shares a key with
  • Persisted under one storage contract
The data journey

How digital twins data reaches one layer.

Walk the path the data takes, from the environment that produces it to the questions it answers. Select a station, or a shape, to read each step.

A twin that is a query over operational data, not a synchronised copy.

Environment

The asset model

Hierarchy, components and relationships recorded once as structure.

Graph · SQL

Data models in play

The shapes, in one layer.

6 shapes carry this domain. Choose a stage to read the operation, or a shape to see every stage that handles it.

PLOMID · Digital Twins model · bind · describe · query Select a stage
Stage

Model

Asset structure, components and relationships

Graph · SQL

Workload map Digital Twins workload map. Every shape on it is a surface of the layer, and each stage names the part of the operation it carries.
  • Time series Measurements and events in time order
  • Graph Relationships and traversal
  • SQL Records, keys and joins
  • JSON / documents Documents and nested objects
  • Vector Similarity and semantic retrieval
  • Objects Large assets with queryable metadata
Where the data goes to work

Questions a fleet asks about itself.

Each one reads telemetry with the records that explain it, from the same layer rather than a sidecar store.

No synchronised copy

The twin is read from the operational layer, which removes the job that keeps a copy in step.

  • Graph
  • SQL

Component-level questions

Hierarchy and measurements are read together, so a component’s state is a query, not a diagram annotation.

  • Time series

Documents in the twin

Manuals and certifications attach to the model elements they describe.

  • JSON / documents
  • Objects

Condition views

Derived indicators are computed over the same measurements they summarise.

  • SQL
  • Vector
Deployment & residency

Where this data is allowed to run.

A twin follows the asset, so where it runs follows where the asset runs.

Deployment, residency and control
What you build next

Digital Twins

An asset model that is read from operational data instead of synchronised with it.

If No synchronised copy is your question, start here.

See Digital Twins Every solution
Next

Where to go next

Solutions The workload answers this industry leans on, with their models and status. Platform The data models in the product today, and the ones extending the layer. Architecture How a request is planned, executed and persisted once it reaches the layer.