Data models

A data model is the shape of one business entity: an order, a customer, an inventory item. It is a field list with a type per field, a description where that helps, and one field marked as the entity's primary key.

Everything downstream leans on it. Workflows map payloads onto it, the warehouse groups records by its primary key, and dashboard widgets offer its fields as things to chart. It is the one place where the messy names your sources use get turned into the names your organization uses.

Data models live under Warehouse in the sidebar. That page lists every model with its Identifier, its record count, and when it was last written to.

Create one

New Data Model offers two routes:

• Create manually — add fields one at a time with names, types, and constraints.
• From JSON Schema — paste a sample JSON object and Hodoflow detects fields automatically.

Manual creation is a three-step wizard: Name & Description, then Add Fields, then Review. The Identifier is generated from the name and is what URLs and API references use. Pick it carefully, because it cannot be changed afterwards.

The import route asks for a Sample JSON Payload and infers one field per top-level key, mapping JSON strings to string, whole numbers to integer, decimals to float, true/false to boolean, and nested objects to map. Anything else, including arrays and nulls, becomes string. Every detected field comes back marked required, and a key called id, a key called email, or a key ending in _id is guessed as the primary key. Nested keys are not walked. Detect Fields → drops you into step one of the same wizard with the results filled in, so you can correct all of that before saving.

The schema editor

Opening a model's Schema page is where the real editing happens. The header carries Usage, + Add Field, Edit Details, and Archive.

Edit Details changes the name and the description. The identifier stays fixed.

The View dropdown switches the section between Fields and JSON Schema — a Draft-7 schema generated from your fields, with a Copy button, which is useful when something outside Hodoflow needs to validate the same shape.

Field types

Six types, and the type you pick decides which constraints and aggregations are available later.

Adding fields

+ Add Field opens a modal with two tabs.

Single takes one field at a time: Field Name (lowercase letters, numbers, and underscores, starting with a letter), an optional Description, the Type, and then the type's own constraint inputs. Save and add another keeps the modal open so you can work down a list.

Two checkboxes matter more than the rest:

• Required — records fail to be created when the field is not populated.
• Primary Key — identifies the business entity for grouping and aggregating records. Only string and integer fields are eligible, and a model can have only one.

Bulk add takes one field per line as name:type[:required][:pk], so pasting a schema someone sent you is a single operation:

email:string:required
age:integer
is_active:boolean
ordered_at:datetime

Type-only lines are accepted and default to optional. Lines starting with # are ignored, and any line that fails to parse is reported with its line number instead of silently dropped.

Changing fields after data exists

Hodoflow protects records that already exist. Once a model has data, a field's type can only widen — integer to float or string, float to string, boolean to string, datetime to string — and the primary key designation cannot be changed at all.

Renaming or deleting a field that a workflow data mapping references is blocked outright, with View usage offered so you can go fix the mappings first.

Who is using this model

Usage answers the question you have before changing anything: every dashboard widget and workflow that references this data model.

The Dashboards tab lists widgets by Widget, Type, Source, and Used on, marking anything that lives in the library but is not currently placed on a dashboard.

The Workflows tab groups by workflow and then by version, showing how many mappings each version has and whether it is active, published, or a draft, with links straight into the builder.

When both tabs are empty you get Not used yet, and it is safe to archive.

Archiving

Archive is a soft delete with a grace period. The model disappears from the default list, and after seven days it and all of its records are permanently deleted. Until then a banner on the page counts down, and Restore brings it back.

Archiving is refused while any dashboard widget or workflow mapping still references the model. Remove or reassign those first — View usage takes you to the list.

Right after archiving, a toast offers Undo. Later, the State filter on the Warehouse list switches between Active and Archived so you can find it again.

Delete now on an archived model skips the wait and removes it and its records immediately. That one cannot be undone.

What comes next

A data model on its own holds nothing. A workflow's Map to Data Model step is what fills it — see Persisting data for writing the mappings, and Dashboards for charting the result.