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E-commerce

Carts, orders and inventory answered in the same breath.

Commerce is a catalogue problem and an event problem: the product data keeps changing shape, and every session and order writes events that must be reconstructable.

See Transactional Systems All of Enterprise & Commerce

A catalogue that changes shape daily and an order book that must never be wrong.

The story

A catalogue that changes shape daily and an order book that must never be wrong.

Where it starts

Orders and payments

Carts, orders, tenders and refunds as records. It is the first of 4 workloads running in E-commerce.

The question it raises

Catalogue that moves

Per-product fields live as documents, so a new attribute does not require a migration.

Why one question is hard

From Browse to Measure

E-commerce data moves through 4 stages — Browse → Order → Fulfil → Measure. The shapes in play are SQL, JSON / documents, Objects, Events, Time series, and answering one question means reading across all of them.

What PLOMID contributes

Commerce asks for flexibility and exactness in the same request. These are the parts that allow it.

The environment

Orders, catalogues, inventory, sessions and fulfilment events.

Catalogue and per-product attributes change constantly, which makes documents the practical shape; orders and inventory need structured accuracy. PLOMID holds both, with session and fulfilment events beside them, so a customer question is answered from one system.

The data journey

How e-commerce 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 catalogue that changes shape daily and an order book that must never be wrong.

Environment

The catalogue

Products, variants and attributes that change faster than any schema.

JSON / documents

One environment · many workloads

What runs against e-commerce data.

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

Carts, orders, tenders and refunds as records.

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

Questions customers force you to answer.

Each one spans the event and the record around it, answered from the same layer rather than joined by hand.

Catalogue that moves

Per-product fields live as documents, so a new attribute does not require a migration.

  • JSON / documents
  • Objects

Order to shipment

Orders, reservations and fulfilment events resolve in one request.

  • SQL

Peak without a separate replica

Snapshot reads let analytics run against the same system that serves the storefront.

  • Events
  • SQL

Search signals as data

Queries and failures are stored beside the catalogue that produced them.

  • Time series
Workload architecture

From event to record.

The work, the shapes it names and the path a request takes — from the storefront to the warehouse.

E-commerce · workload architecture
Workloads

What runs against this data.

  • Orders and payments
  • Catalogue and content
  • Inventory and fulfilment
  • Session and search signals
Data models

The shapes those workloads read and write.

  • SQL
  • JSON / documents
  • Objects
  • Events
  • Time series
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
Data models in play

The shapes, in one layer.

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

PLOMID · E-commerce browse · order · fulfil · measure Select a stage
Stage

Browse

Catalogue, attributes and media

JSON / documents · Objects

Workload map E-commerce workload map. Every shape on it is a surface of the layer, and each stage names the part of the operation it carries.
  • SQL Records, keys and joins
  • JSON / documents Documents and nested objects
  • Objects Large assets with queryable metadata
  • Events Operational events as they happen
  • Time series Measurements and events in time order
Deployment & residency

Where this data is allowed to run.

Peak traffic arrives without notice, so read consistency under write load is a design requirement.

Deployment, residency and control
What you build next

Transactional Systems

Application records with consistent reads and writes while reports run against them.

If Catalogue that moves is your question, start here.

See Transactional Systems 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.