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Data Table Connector
Create your own typed data tables and perform insert/get/find/update/upsert/delete/bulk-upsert operations on them from a workflow — platform-managed storage scoped to your store.
Browse 7 Data Table actions databaseOn this page
What this connector is for
Reads and writes your own data tables: platform-managed persistent storage scoped to your store, like a lightweight per-workflow database. No connection is needed. Like the Variable and Cache connectors, this is platform-internal state keyed off your store automatically.
A table (created and managed on the designer's Data Tables page, see Managing data tables, not by this connector) has a fixed schema: an ordered list of typed fields, with one or more fields designated as the (possibly composite) primary key. Field types are string, integer, float, boolean, array, json, enum, object and objectArray. Only string, integer, float, boolean and enum can be primary-key components. Types are enforced strictly: writing a number to a string field (or vice versa) fails validation rather than coercing. A field marked isSearchable gets a live index and can be filtered on by Find Records (max 5 searchable fields per table); other fields can't be filtered.
Every action returns a plain result, read as {{<stepReference>.response.data.<field>}}. None of them halt the workflow with an HTTP-style error response: a lookup miss or bad primary key surfaces as a thrown error visible in execution logs. Primary-key fields are ordinary fields on the record and are never stripped from a returned data object.
Every action, with its fields, is listed in the action reference.
Insert Record
Creates a record and fails with a conflict error if one already exists at the primary key derived from your data. Validation is in "complete" mode: every required field without a default must be present. Response: {{<stepReference>.response.data.data}} (the stored fields), plus createdAt and updatedAt.
Get Record
A raw point lookup by exact primary key, fast regardless of table size. There is no "found" flag: {{<stepReference>.response.data.data}} is null when no record exists, and createdAt/updatedAt are then absent. Branch on data being null.
Find Records
Lists a table's records, optionally filtered on searchable fields, using keyset (cursor) pagination rather than offset, so paging stays fast deep into a large table.
- Filter entries look like
{"status": {"operator": "equals", "value": "active"}}.equalsworks on any searchable type (the value is coerced to the field's type).contains,startsWith,endsWithandlikework on string/enum fields only and are case-insensitive.likealso accepts wildcards:%or*for any run of characters,_or?for exactly one. - Filtering a non-searchable field, or using a string operator on a non-string field, fails the step.
- Page size defaults to 20, max 100.
Response: {{<stepReference>.response.data.items}} is an array of {data, createdAt, updatedAt}; {{<stepReference>.response.data.nextCursor}} is passed back as the cursor for the next page and is absent or empty on the last page.
Update Record
Partially patches a record that must already exist. Fields you omit are untouched, and other required fields are not re-checked (validation is "partial" mode). If nothing exists at the primary key it throws a 404-style error; use Upsert when the record may not exist. Response: the full post-update fields at {{<stepReference>.response.data.data}}.
Upsert Record
Creates the record if its primary key is new, or fully replaces its data if it exists. It is a single atomic database operation, so no locking is needed under concurrent calls. The key is derived from the primary-key fields present in the record data. Unlike Update this is a wholesale replace, validated in "complete" mode.
{{<stepReference>.response.data.created}} is true if this call created the record and false if it replaced one; data, createdAt and updatedAt are also returned.
Delete Record
Removes a record by primary key. {{<stepReference>.response.data.success}} is true on success. Deleting a key that doesn't exist throws a 404-style error rather than returning false.
Bulk Upsert Records
Upserts many records in one chunked, unordered bulk write, each matched on its own primary key. One bad row (for example failing type or required-field validation) is reported without blocking the rest. Prefer it over Upsert in a loop for an import or sync of more than a handful of records.
{{<stepReference>.response.data.upserted}}: count of records created or updated.{{<stepReference>.response.data.errors}}: array of{index, message}for skipped rows;indexis the position in the input array.
Common tasks
Look up, then create or update: use Get Record, then branch on {{getCustomer.response.data.data}} being null. If you don't need the branch, a single Upsert does the same thing atomically.
Page through a whole table: call Find Records in a loop, feeding {{findOrders.response.data.nextCursor}} back as the cursor until it comes back empty.
Also applies here
Step Name
What it's for
Every step in a workflow gets a name — either one you set or a default based on the connector and action (e.g. "Get Order Details", "Send Welcome Email"). It's shown throughout the UI and in your execution history, and it's also the source for the step's Reference — a camelCase identifier auto-generated from the name (e.g. "Get Order Details" → getOrderDetails) — which is what you actually use in {{...}} expressions to read this step's output from later steps. See Step Reference.
Rules
- Must be at least 2 characters, and 50 characters or fewer.
- Must be unique within the workflow — reusing a name that's already taken will be rejected, with a suggested alternative (e.g.
"Get Order Details 2"). - Can't be empty.
Tips
- Prefer a descriptive, human-readable name over a generic one — "Get Order Details" is easier to work with later than "HTTP Request 2", especially once a workflow has a dozen steps.
- Renaming a step updates every reference to it elsewhere in the workflow automatically.
Step Reference
Syntax
Any input field can reference earlier data using {{expression}}. The expression is evaluated as JSONata — so simple dot-paths and more advanced queries (filters, functions) both work.
Referencing a step's output
Use the step's Reference — a camelCase identifier auto-generated from its Name (e.g. "Get Order Details" → getOrderDetails), shown read-only wherever the step's fields are configured — followed by the field path. Elsewhere in these docs this general pattern is written as {{<stepReference>.field.path}}:
{{getOrderDetails.response.data.id}}
{{getOrderDetails.response.status}}
The raw display name won't work here even though it's what you see in the UI — {{Get Order Details.response.data.id}} isn't valid, since a bare name containing spaces isn't a single JSONata identifier. Always use the camelCase Reference.
You can also reference steps by position instead of by reference:
{{steps[0].response.data.id}}
Referencing trigger data
{{trigger.headers.authorization}}
{{trigger.body.customerId}}
{{trigger.query.page}}
{{trigger.params.orderId}}
{{trigger.method}}
{{trigger.path}}
Referencing workflow variables
{{variables.myVariable}}
See Variables for the full list of variable types and more examples, including connection-type variables.
Referencing runtime variables
A separate, mutable namespace written by the Variable connector while a run is in progress — not the same as the workflow-level variables above:
{{runtimeVariables.myVariable}}
Notes
- If an expression can't be resolved (a typo in a step name, a field that doesn't exist), it resolves to an empty string rather than failing the workflow — check your execution history if a value comes through blank.
- Object values are automatically JSON-stringified when interpolated into a string field.
Execution Settings
Fire-and-forget
When enabled, the workflow doesn't wait for this step to complete before moving to the next one. Use it for steps whose result nothing downstream depends on — logging, analytics, notifications — so they don't add latency to the steps that matter.
Continue on error
When enabled, a failure in this step doesn't stop the workflow — execution continues to the next step. The failure is still recorded in the execution history; this just controls whether it's fatal.
Combine the two for steps that are genuinely optional to the outcome: fire-and-forget so they don't add latency, continue-on-error so a failure in them (e.g. an analytics endpoint being briefly down) doesn't take down an otherwise-successful workflow run.
Caching
What it does
When enabled, a step's result is cached for a configurable TTL (time-to-live, in seconds). If the step runs again with the same effective cache key before the TTL expires, the cached result is returned instead of re-running the step.
Configuring it
- Enabled — turn caching on or off for this step.
- TTL — how long (in seconds) a cached result stays valid.
- Cache key template — an expression (supporting the same
{{...}}step reference syntax used elsewhere) that determines what counts as "the same call". By default this is based on the step's resolved input; a custom template lets you cache more narrowly or broadly than that.
When to use it
Good candidates are steps that call something slow or rate-limited but return the same answer for the same input within a short window — a lookup against a rarely-changing external system, for example. Skip it for steps whose result must always be fresh (anything involving live inventory, pricing, or payment state).
Locking
What it does
When enabled, only one execution of this step (for a given lock key) can run at a time. If a second execution tries to run the same step while a lock is held, it waits until the lock is released or the hold period elapses.
Configuring it
- Enabled — turn locking on or off for this step.
- Lock key — an expression (supporting the same
{{...}}step reference syntax used elsewhere) that determines what counts as "the same resource". By default the lock is scoped to the step itself; a custom key lets you lock per-customer, per-order, or any other identifier that needs serialized access. - Period — how long (in seconds) the lock is held before it's automatically released, in case an execution doesn't complete normally.
When to use it
Use it whenever concurrent executions could race on the same resource — e.g. two workflow runs both trying to update the same order's status at once. A lock key scoped to the order id ensures only one of them proceeds at a time.
Last updated 9 October 2026