Data Fetcher

What it is

Data Fetcher is an Airtable extension that lets you connect to third-party applications and APIs from inside your base. Its own about page calls it easy to get started for no-coders but flexible for more technical users. It is a data import and sync tool for Airtable, so the person it serves is someone who already builds on Airtable: an operations or marketing lead, a founder running a product from a base, or a freelancer building client systems.

The company behind it is Influence Grid Ltd, trading as Data Fetcher and registered in England and Wales. The about page calls it bootstrapped and profitable, in its 6th year, serving 100s of customers and 1000s of users. It says Data Fetcher was one of the first extensions on the Airtable marketplace and has since been featured by Airtable and G2.

What you build and how

You build data feeds. A feed, which Data Fetcher calls a request, pulls data from an outside source, transforms it and writes it into your Airtable tables. The home page puts the idea as "No-code and low-code backend: bring your data into Airtable and power your no-code or low-code app", and "Streamline your operations: fewer tools and databases to manage. Run your product from inside Airtable."

There are two ways to start. The first is the ready-made integrations. The about page says these connect to dozens of applications like OpenAI, Google Analytics and Facebook Ads, and the integrations page groups examples by theme, including AI, marketing, database and spreadsheet, accounting and finance. The home page shows Google Sheets imports, Xero, and Stripe customers and subscriptions. It also lists AI integrations: ChatGPT to generate text and images with ChatGPT and DALL-E, Claude to generate text with Anthropic's Claude models, OCR to extract text from images, and a general generative AI option.

The second way is a custom request. The about page says custom requests connect to any REST or GraphQL API, or import remote CSV, XML or RSS files. The integrations page repeats that Data Fetcher can connect to most REST and GraphQL APIs and pull data into Airtable on a schedule, even when Airtable has no native integration for the tool. This is the escape hatch for a vendor nobody built a connector for.

Scheduling is the sync part. The automation page says data can be synced on a schedule or as part of your workflows without scripts or custom code. Scheduled requests run in the background even when you are not logged into Airtable. Schedules range from minutes to days depending on your plan. Where Airtable's own automations fall short, the page's case is that they handle triggers and internal workflows well but start to struggle when a flow depends on external data, which otherwise calls for custom scripts. The company positions Data Fetcher as complementary, and says many teams use both.

The two meet through a webhook. Every Data Fetcher request has a webhook URL, so an Airtable automation can trigger it when records change, when conditions are met or when a form is submitted. You can connect APIs, schedule requests and trigger workflows using a visual interface inside Airtable, because Data Fetcher runs as a native Airtable extension.

Code is optional. The integrations page says many integrations need none, and that code becomes useful for custom logic, unusual authentication, complex transformations or full control over how data is fetched and updated.

One practical rule appears on the integrations page. To avoid duplicates when data refreshes, use a stable identifier from the source, such as an ID, email address or unique reference, to match incoming data to existing records. Without a consistent key, refreshes tend to create new rows instead of updating the right ones.

What do you do with the data once it is in? The home page lists the follow-on uses: build internal tools for teams that draw on as many external sources as you need, create reports and dashboards with Airtable's data visualization tools, and create customized applications with Airtable's Interface Designer. The use-cases page lists the kinds of Airtable systems people build: CRM pipelines, project management, inventory tracking, marketing reporting, SEO dashboards, ads reporting dashboards and web scraping workflows. It frames the shift this way: with live data feeds and automation, a base becomes a central operating system for your business instead of a static database.

The navigation lists feature pages for Airtable integrations, importing data to Airtable, Airtable automation, Airtable ETL, Airtable generative AI and Airtable dashboards. Resources include a help center, video tutorials and a blog.

The evidence from the pages

The pricing page is built around 3 counters. A run is one API request, and each fetch counts as one. Running across multiple Airtable records or paginated data uses additional runs, one per record or page. Failed requests do not count toward the limit. A response record is an individual data item created when Data Fetcher transforms an API response for Airtable, so 100 items from an API count as 100 response records, even if none changes anything in your base. A response field is a data point you map from an API response to an Airtable field. The page gives an example that the Pro plan lets you select up to 150 individual fields to import per request.

There is a free plan, and the page says it never expires. It allows 100 runs and 10,000 response records per month. The page also says there is no free trial, since the free plan is the way to test. You sign up for a free account in the extension and click Upgrade on the home screen to choose a paid plan. The page names Pro, Business and Business + among the paid plans, and says team members can be added on those three. Dollar prices and per-plan limits are best read on the live pricing page. When you hit your limit, scheduled runs are paused.

Billing is handled by Stripe, and the company says it never sees or stores your card details. It says it does not currently offer discounts, because it aims for fair and sustainable prices as a small company.

The customer and user counts above are the company's own claims.

Who it suits and who it does not

Data Fetcher suits an Airtable-centered team that wants outside data in its base on a timer: ad spend from Facebook Ads, traffic from Google Analytics, payments from Stripe or text from an AI model, without writing and hosting a script. A solo builder can test it on the free plan. An agency building client systems gets a way to reach any REST or GraphQL API.

It is built around Airtable. Everything lands in Airtable tables, so it will not help a team that has left Airtable, and its pitch is data into Airtable rather than out of it. Usage is metered in runs and records, and a feed that fetches per record or per page can use runs quickly. The free plan's 100 runs a month is enough to try one or two feeds. And a source with no API and no file export has nothing for Data Fetcher to call.