---
title: Table
description: User-defined data tables for storing and querying structured data
---

import { BlockInfoCard } from "@/components/ui/block-info-card"

<BlockInfoCard
  type="table"
  color="#10B981"
/>

{/* MANUAL-CONTENT-START:intro */}
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
{/* MANUAL-CONTENT-END */}

## 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:

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

Use `$or` for OR logic:

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

## Sort Specification

Specify sort order with column names and direction:

```json
{
  "createdAt": "desc"
}
```

Multi-column sorting:

```json
{
  "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
