---
title: Tables
description: Tables store structured data — columns as types, rows as entries — a spreadsheet or lightweight database your workflows read, write, and operate on at scale.
---

import { VideoPlaceholder } from '@/components/ui/video-placeholder'
import { WhatYouWillLearn } from '@/components/ui/what-you-will-learn'
import { VideoChapters } from '@/components/ui/video-chapters'
import { WorkflowPreview, TABLE_ENRICH_WORKFLOW } from '@/components/workflow-preview'

<VideoPlaceholder eyebrow="Tables" title="Tables" src="https://nnjgp7vypgx4myuq.public.blob.vercel-storage.com/academy-preview/tables-light-with-intro.mp4" className="mt-2" />

<div className="mt-8 grid grid-cols-1 items-start gap-10 lg:grid-cols-[1fr_300px]">
<div>

A **table** stores structured data: columns are the types, rows are the entries. Think of it as giving your workflows a spreadsheet — or a lightweight database — for tracking and maintaining records.

<WhatYouWillLearn
  items={[
    {
      title: 'The shape of a table',
      body: 'Columns define types, rows hold entries — the same mental model as a spreadsheet your workflows can read and write.',
    },
    {
      title: 'Work as operations over data',
      body: 'Many business use cases are just a query, an update, or a combination with logic over structured records.',
    },
    {
      title: 'Scale with workflow columns',
      body: 'Workflow columns run an operation across every row in parallel, making a table a surface for automation at scale.',
    },
  ]}
/>

</div>

<VideoChapters
  chapters={[
    { title: 'Introduction', time: '0:00' },
    { title: 'What a table is', time: '0:26' },
    { title: 'Rows and fields', time: '0:35' },
    { title: 'Using it in a workflow', time: '0:42' },
    { title: 'Reading rows', time: '0:51' },
    { title: 'Writing rows', time: '1:01' },
    { title: 'Seeing it in the logs', time: '1:12' },
    { title: 'Tables as a queue', time: '1:21' },
  ]}
/>

</div>

## A familiar shape

If you've used a spreadsheet, you already understand a table: columns with types, rows of entries. Your workflows read rows to work on, write rows they produce, and update rows in place.

Here's the shape of it — a workflow that reads a table, operates on each record, and writes the result back:

<WorkflowPreview workflow={TABLE_ENRICH_WORKFLOW} />

## Operations over data

A surprising amount of real business work decomposes into a few operations over structured records:

- **A query** — "which leads are still unprocessed?"
- **An update** — "mark these rows handled."
- **A combination with logic** — "for each new signup, score it, then write the score back."

Once you see a use case that way, building it in Sim is mostly wiring those operations together.

## A surface for scale

Tables aren't only storage — they're a working surface for your AI systems. **Workflow columns** let you run an operation across every row at once, in parallel, so a table becomes the place you launch and track work in bulk.

That makes a table a powerful interface for automation — the place you manage and operate agentic processes at scale.

## Related documentation

- [Tables overview](/tables)
- [Using tables in workflows](/tables/using-in-workflows)
- [Workflow columns](/tables/workflow-columns)
