Filter

Type key: filter
Group: Data
Category: data
Tier: CORE

The Filter node removes items from an array based on one or more conditions. It is a declarative, non-destructive way to narrow down datasets without writing code.

Handles

Handle	Direction	Description
input	Input	Receives the data array to filter
output	Output	Emits the filtered array

Configuration

Field	Type	Default	Description
conditions	array	[]	Array of condition objects
logic	enum	AND	How conditions are combined: AND or OR

Condition Object

{
    "type": "equals",
    "data": { "field": "data.status", "value": "active" },
    "logic": "AND"
}

Property	Description
type	Comparison operator (slug format)
data.field	Dot-notation path to the field in each array item
data.value	Value to compare against
logic	Logic connector with next condition: AND or OR

Smart Type Inference

The Filter node automatically detects data types from upstream JSON values and adapts the UI accordingly:

Detected type	How detected	Operators shown	Value input
Number	typeof value === 'number' in JSON	=, !=, >, <, >=, <=, in, not_in, is_null, is_not_null	Text input
String	typeof value === 'string' in JSON	=, !=, contains, not_contains, starts_with, ends_with, in, not_in, is_null, is_not_null	Select from upstream values or text input (toggle with ⚡)
Boolean	typeof value === 'boolean' in JSON	=, !=, is_null, is_not_null, is_true, is_false	True/False dropdown
Date	Field name ends with _at or _date	is_exactly, is_not, is_after, is_before, is_in_the_past, is_today, is_within_X_days	Date picker

When connected to a Data Model node, field types are inferred from the database column types via the model schema.

Value Picker (⚡)

For string fields, the value input shows a select dropdown with distinct values extracted from upstream JSON data. Click the ⚡ icon to toggle between:

• Select mode: pick from available values
• Manual mode: enter free text or dynamic expressions like {{variable}}

Supported Operators

Operator	Description
equals	Strict equality
not_equals	Not equal
greater_than	Numeric >
less_than	Numeric <
greater_than_or_equal	Numeric >=
less_than_or_equal	Numeric <=
contains	String contains substring
not_contains	String does not contain
starts_with	String starts with
ends_with	String ends with
in	Value is in a comma-separated list
not_in	Value is not in list
is_null	Value is null
is_not_null	Value is not null
is_empty	Null, empty string, or empty array
is_not_empty	Not null and not empty
is_in_the_past	Date is in the past
is_in_the_future	Date is in the future
is_today	Date is today
is_within_days	Date within X days from now
is_within_months	Date within X months from now
is_older_than_days	Date older than X days
is_older_than_months	Date older than X months

Logic Modes

AND (default)

All conditions must be satisfied for an item to pass:

Field: data.status  = active
AND
Field: data.score   > 50

Only items where both status = active AND score > 50 are included.

OR

At least one condition must be satisfied:

Field: data.status  = active
OR
Field: data.status  = trial

Items where status is either active OR trial are included.

Input Detection

The Filter node automatically detects the array to filter:

1. If input has a data key with an array → filters data
2. If input itself is a flat array → filters it directly

The structure is preserved in the output (i.e., if the input had a data key, the output also has a data key).

Field Path Resolution

Field paths use dot notation from the root JSON (e.g., data.status, data.lifetime_value). When evaluating conditions against individual items already extracted from a collection, the Filter node progressively strips leading path segments to find the correct value.

Output

Given input:

{
    "data": [
        { "id": 1, "status": "active", "score": 80 },
        { "id": 2, "status": "inactive", "score": 90 },
        { "id": 3, "status": "active", "score": 30 }
    ]
}

With conditions: data.status = active AND data.score > 50

Output:

{
    "data": [{ "id": 1, "status": "active", "score": 80 }],
    "count": 1
}

Preset Example

💾 Try this example

Download the workflow JSON — open an empty workflow and import the file.

Examples

Filter Active High-Value Customers

Logic: AND
Conditions:
    - data.status         equals          active
    - data.lifetime_value greater_than    500

Filter Items with Missing Email

Logic: AND
Conditions:
    - data.email  is_not_empty

Filter by Multiple Statuses (OR)

Logic: OR
Conditions:
    - data.status  equals  pending
    - data.status  equals  processing

Notes

• If no conditions are configured, all input data passes through unchanged
• The Filter node does not modify the items it passes — only includes/excludes them
• Operators shown in the UI adapt based on the detected field data type
• For transforming item fields, use the Transform node
• For a single conditional branch (not array filtering), use the If node