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Data Tables in n8n

Automation often needs more than just nodes and triggers; it needs a place to store and manage data across workflows. That’s exactly why n8n introduced Data Tables πŸ—‚οΈ, a lightweight database built right into the platform.

In this article, let’s break down What, Where, When, Why, and How to use Data Tables, along with their pros, cons, examples, limitations, and prerequisites.

What are Data Tables in n8n?

Data Tables are built-in structured storage inside n8n.
Think of them as a mini-database where you can:

  • Save records across workflows

  • Query and update data easily

  • Avoid the hassle of managing an external DB

Where can you use them?

  • In workflows, as a shared state

  • For lead management across automations

  • In AI workflows, to store conversation history or embeddings

  • As a mini CRM or log tracker inside n8n

When should you use Data Tables?

  • When you need data persistence beyond a single execution

  • When you want a lookup table (e.g., product SKUs, promo codes)

  • When prototyping fast without setting up SQL/Mongo

  • When you want to log results centrally for reports

Examples

  1. Lead management β†’ Store scraped leads and update their status as workflows progress.

  2. Temporary state tracking β†’ Keep intermediate results like tokens, logs, or workflow checkpoints.

  3. Configuration management β†’ Save API keys, mapping rules, or campaign metadata.

  4. Batch processing β†’ Store records to process later in smaller chunks.

Why use Data Tables?

  • Zero setup – no extra infra

  • Accessible across multiple workflows

  • Lightweight but powerful for small to medium use cases

  • Perfect for rapid prototyping & internal tools

  • Avoid dependency on external databases for small to medium data.

  • Simplify state management (no more storing values in Google Sheets just to pass data around).

How to use Data Tables in n8n?

  1. Navigate to Resources β†’ Data Tables

  2. Create a new table with schema (e.g., id, name, email)

  3. Use the Data Table node in workflows:

    • Insert, Update, and Delete records

    • Query & filter data

  4. Connect to Gmail, Slack, Twilio, or AI nodes

Pros

  • Native feature (no DB required)

  • Easy to manage & share across workflows

  • Good for prototyping & automation logs

  • Reduces dependency on external services

Cons

  • Limited compared to SQL/Mongo (no joins, no complex queries)

  • Not ideal for very large datasets

  • Still evolving (new feature in n8n)

Examples

  • CRM Lite β†’ Collect leads from Google Sheets β†’ Store in Data Table β†’ Send follow-up emails.

  • AI Context Storage β†’ Save chat history β†’ Feed into AI node β†’ Continue conversation seamlessly.

  • Notification Tracker β†’ Store all email/SMS sent logs β†’ Use later for reports.

Limitations

  • Not built for heavy transactional apps

  • No advanced features like triggers/indexes

  • Suitable mostly for small to medium workflow data

Setup & Access

  • Available in the n8n UI (left sidebar).

  • Works both in n8n Cloud and self-hosted setups.

  • Multiple workflows can use the same table.

  • Data persists across executions until explicitly deleted.

Prerequisites

  • The latest version of n8n is installed

  • Basic knowledge of nodes & JSON mapping

  • An automation use case needing shared data

Security & Access Control

  • In n8n Cloud, only your workspace/team can access Data Tables.

  • In self-hosted setups, access is limited to your instance.

  • Use environment variables or secrets for sensitive configs instead of storing in Data Tables.

n8n-Datatables

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