Table

Tables allow you to create and manage custom data tables directly within Cadense. Store, query, and manipulate structured data within your workflows without needing external database integrations.

Why Use Tables?

No external setup: Create tables instantly without configuring external databases
Workflow-native: Data persists across workflow executions and is accessible from any workflow in your workspace
Flexible schema: Define columns with types (string, number, boolean, date, json) and constraints (required, unique)
Powerful querying: Filter, sort, and paginate data using MongoDB-style operators
Agent-friendly: Tables can be used as tools by AI agents for dynamic data storage and retrieval

Key Features:

Create tables with custom schemas
Insert, update, upsert, and delete rows
Query with filters and sorting
Batch operations for bulk inserts
Bulk updates and deletes by filter
Up to 10,000 rows per table, 100 tables per workspace

Creating Tables

Tables are created from the Tables section in the sidebar. Each table requires:

Name: Alphanumeric with underscores (e.g., customer_leads)
Description: Optional description of the table's purpose
Schema: Define columns with name, type, and optional constraints

Column Types

Type	Description	Example Values
`string`	Text data	`"John Doe"`, `"active"`
`number`	Numeric data	`42`, `99.99`
`boolean`	True/false values	`true`, `false`
`date`	Date/time values	`"2024-01-15T10:30:00Z"`
`json`	Complex nested data	`{"address": {"city": "NYC"}}`

Column Constraints

Required: Column must have a value (cannot be null)
Unique: Values must be unique across all rows (enables upsert matching)

Usage Instructions

Create and manage custom data tables. Store, query, and manipulate structured data within workflows.

Tools

`table_query_rows`

Query rows from a table with filtering, sorting, and pagination

Input

Parameter	Type	Required	Description
`tableId`	string	Yes	Table ID
`filter`	object	No	Filter conditions using MongoDB-style operators
`sort`	object	No	Sort order as {column: "asc"\|"desc"}
`limit`	number	No	Maximum rows to return (default: 100, max: 1000)
`offset`	number	No	Number of rows to skip (default: 0)

Output

Parameter	Type	Description
`success`	boolean	Whether query succeeded
`rows`	array	Query result rows
`rowCount`	number	Number of rows returned
`totalCount`	number	Total rows matching filter
`limit`	number	Limit used in query
`offset`	number	Offset used in query

`table_insert_row`

Insert a new row into a table

Input

Parameter	Type	Required	Description
`tableId`	string	Yes	Table ID
`data`	object	Yes	Row data as JSON object matching the table schema

Output

Parameter	Type	Description
`success`	boolean	Whether row was inserted
`row`	object	Inserted row data including generated ID
`message`	string	Status message

`table_upsert_row`

Insert or update a row based on unique column constraints. If a row with matching unique field exists, update it; otherwise insert a new row.

Input

Parameter	Type	Required	Description
`tableId`	string	Yes	Table ID
`data`	object	Yes	Row data to insert or update

Output

Parameter	Type	Description
`success`	boolean	Whether row was upserted
`row`	object	Upserted row data
`operation`	string	Operation performed: "insert" or "update"
`message`	string	Status message

`table_batch_insert_rows`

Insert multiple rows at once (up to 1000 rows per batch)

Input

Parameter	Type	Required	Description
`tableId`	string	Yes	Table ID
`rows`	array	Yes	Array of row data objects to insert

Output

Parameter	Type	Description
`success`	boolean	Whether batch insert succeeded
`rows`	array	Array of inserted rows with IDs
`insertedCount`	number	Number of rows inserted
`message`	string	Status message

`table_update_row`

Update a specific row by its ID

Input

Parameter	Type	Required	Description
`tableId`	string	Yes	Table ID
`rowId`	string	Yes	Row ID to update
`data`	object	Yes	Data to update (partial update supported)

Output

Parameter	Type	Description
`success`	boolean	Whether row was updated
`row`	object	Updated row data
`message`	string	Status message

`table_update_rows_by_filter`

Update multiple rows matching a filter condition

Input

Parameter	Type	Required	Description
`tableId`	string	Yes	Table ID
`filter`	object	Yes	Filter to match rows for update
`data`	object	Yes	Data to apply to matching rows
`limit`	number	No	Maximum rows to update (default: 1000)

Output

Parameter	Type	Description
`success`	boolean	Whether update succeeded
`updatedCount`	number	Number of rows updated
`updatedRowIds`	array	IDs of updated rows
`message`	string	Status message

`table_delete_row`

Delete a specific row by its ID

Input

Parameter	Type	Required	Description
`tableId`	string	Yes	Table ID
`rowId`	string	Yes	Row ID to delete

Output

Parameter	Type	Description
`success`	boolean	Whether row was deleted
`deletedCount`	number	Number of rows deleted (1 or 0)
`message`	string	Status message

`table_delete_rows_by_filter`

Delete multiple rows matching a filter condition

Input

Parameter	Type	Required	Description
`tableId`	string	Yes	Table ID
`filter`	object	Yes	Filter to match rows for deletion
`limit`	number	No	Maximum rows to delete (default: 1000)

Output

Parameter	Type	Description
`success`	boolean	Whether delete succeeded
`deletedCount`	number	Number of rows deleted
`deletedRowIds`	array	IDs of deleted rows
`message`	string	Status message

`table_get_row`

Get a single row by its ID

Input

Parameter	Type	Required	Description
`tableId`	string	Yes	Table ID
`rowId`	string	Yes	Row ID to retrieve

Output

Parameter	Type	Description
`success`	boolean	Whether row was found
`row`	object	Row data
`message`	string	Status message

`table_get_schema`

Get the schema definition for a table

Input

Parameter	Type	Required	Description
`tableId`	string	Yes	Table ID

Output

Parameter	Type	Description
`success`	boolean	Whether schema was retrieved
`name`	string	Table name
`columns`	array	Array of column definitions
`message`	string	Status message

Filter Operators

Filters use MongoDB-style operators for flexible querying:

Operator	Description	Example
`$eq`	Equals	`{"status": {"$eq": "active"}}` or `{"status": "active"}`
`$ne`	Not equals	`{"status": {"$ne": "deleted"}}`
`$gt`	Greater than	`{"age": {"$gt": 18}}`
`$gte`	Greater than or equal	`{"score": {"$gte": 80}}`
`$lt`	Less than	`{"price": {"$lt": 100}}`
`$lte`	Less than or equal	`{"quantity": {"$lte": 10}}`
`$in`	In array	`{"status": {"$in": ["active", "pending"]}}`
`$nin`	Not in array	`{"type": {"$nin": ["spam", "blocked"]}}`
`$contains`	String contains	`{"email": {"$contains": "@gmail.com"}}`

Combining Filters

Multiple field conditions are combined with AND logic:

{
  "status": "active",
  "age": {"$gte": 18}
}

Use $or for OR logic:

{
  "$or": [
    {"status": "active"},
    {"status": "pending"}
  ]
}

Sort Specification

Specify sort order with column names and direction:

{
  "createdAt": "desc"
}

Multi-column sorting:

{
  "priority": "desc",
  "name": "asc"
}

Built-in Columns

Every row automatically includes:

Column	Type	Description
`id`	string	Unique row identifier
`createdAt`	date	When the row was created
`updatedAt`	date	When the row was last modified

These can be used in filters and sorting.

Limits

Resource	Limit
Tables per workspace	100
Rows per table	10,000
Columns per table	50
Max row size	100KB
String value length	10,000 characters
Query limit	1,000 rows
Batch insert size	1,000 rows
Bulk update/delete	1,000 rows

Notes

Category: blocks
Type: table
Tables are scoped to workspaces and accessible from any workflow within that workspace
Data persists across workflow executions
Use unique constraints to enable upsert functionality
The visual filter/sort builder provides an easy way to construct queries without writing JSON

Table

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