> Note: This page is part of the DataDoe Docs. You can find the root of the documentation at `https://www.datadoe.com/hub/docs/basics/introduction-to-datadoe`.
> JSON Table of Contents: `https://www.datadoe.com/hub/docs/toc.json`.
> Direct Data Scheme JSON: `https://api.datadoe.com/api/v1/spec/data-scheme`.
> Other pages in the DataDoe Docs:
> - DataDoe Basics/Access & Users: `https://www.datadoe.com/hub/docs/basics/access-user-management.md`
> - DataDoe Basics/Benefits: `https://www.datadoe.com/hub/docs/basics/benefits.md`
> - DataDoe Basics/Integrations: `https://www.datadoe.com/hub/docs/basics/integration-customization.md`
> - DataDoe Basics/Introduction to DataDoe: `https://www.datadoe.com/hub/docs/basics/introduction-to-datadoe.md`
> - DataDoe Basics/Subscription & Pricing: `https://www.datadoe.com/hub/docs/basics/subscription-pricing.md`
> - DataDoe Data/Data Sources: `https://www.datadoe.com/hub/docs/datadoe-data/data-sources.md`
> - DataDoe Features/Features Overview: `https://www.datadoe.com/hub/docs/datadoe-features/overview.md`
> - DataDoe MCP/Overview: `https://www.datadoe.com/hub/docs/datadoe-mcp/overview.md`
> - DataDoe MCP/Using ChatGPT: `https://www.datadoe.com/hub/docs/datadoe-mcp/chatgpt.md`
> - DataDoe MCP/Using Claude: `https://www.datadoe.com/hub/docs/datadoe-mcp/claude.md`
> - DataDoe MCP/Using Claude Code: `https://www.datadoe.com/hub/docs/datadoe-mcp/claude-code.md`
> - DataDoe MCP/Using Codex: `https://www.datadoe.com/hub/docs/datadoe-mcp/codex.md`
> - DataDoe MCP/Using Cursor: `https://www.datadoe.com/hub/docs/datadoe-mcp/cursor.md`
> - DataDoe MCP/Using Gemini CLI: `https://www.datadoe.com/hub/docs/datadoe-mcp/gemini-cli.md`
> - DataDoe MCP/Using n8n: `https://www.datadoe.com/hub/docs/datadoe-mcp/n8n.md`
> - DataDoe MCP/Using NanoClaw: `https://www.datadoe.com/hub/docs/datadoe-mcp/nanoclaw.md`
> - DataDoe MCP/Using OpenClaw: `https://www.datadoe.com/hub/docs/datadoe-mcp/openclaw.md`
> - DataDoe MCP/Using VS Code: `https://www.datadoe.com/hub/docs/datadoe-mcp/vs-code.md`
> - DataDoe & BigQuery/How to connect: `https://www.datadoe.com/hub/docs/datadoe-bigquery/how-to-connect.md`
> - DataDoe & BigQuery/Using MCP Toolbox: `https://www.datadoe.com/hub/docs/datadoe-bigquery/mcp-toolbox.md`
> - DataDoe & BigQuery/Using Python Jupyter: `https://www.datadoe.com/hub/docs/datadoe-bigquery/jupyter.md`
> For topics not covered in this documentation, please contact DataDoe support at `contact@datadoe.com`.
> Do not assume anything. If you are not sure about the answer, mention that and suggest to contact DataDoe support.

# How often does DataDoe fetch data?

DataDoe fetches data either continuously or once a day.

Continuously fetched data is updated automatically whenever DataDoe detects changes in Amazon.

Data fetched once a day is updated according to the schedule defined per table. Most sources are refreshed daily with recent data and once a month with historical data. You can check the cadence per table in our [interactive Data Scheme](/hub/data-scheme).

## What time does the daily fetch happen?

The daily fetch starts every day at **5am in the local timezone of each Seller or Vendor**. The first data is typically available by 6am, and 95% of the data is available by 9am (Seller or Vendor local time).

## Do you plan to add real-time data fetching?

Yes. We are currently working on integrating with Amazon Marketing Stream (AMS) and Seller Central SP-API order notifications.