Table

Tables allow you to create and manage custom data tables directly within Sim. 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

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.

Actions

table_insert_row

Insert a new row into a table. IMPORTANT: You must use the

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Output

table_batch_insert_rows

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Output

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. IMPORTANT: You must use the

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Output

table_update_row

Update an existing row in a table. Supports partial updates - only include the fields you want to change. IMPORTANT: You must use the

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Output

table_update_rows_by_filter

Update multiple rows that match filter criteria. Data is merged with existing row data.

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Output

table_delete_row

Delete a row from a table

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Output

table_delete_rows_by_filter

Delete multiple rows that match filter criteria. Use with caution - supports optional limit for safety.

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Output

table_query_rows

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

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Output

table_get_row

Get a single row by ID

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Output

table_get_schema

Get the schema configuration of a table

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Output

Filter Operators

Filters use MongoDB-style operators for flexible querying:

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:

These can be used in filters and sorting.

Limits

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