How to Integrate Hevo Data with Your Headless CMS

What is Hevo Data?

Hevo Data is a cloud ELT platform that moves data from SaaS apps, databases, files, and webhooks into destinations like Snowflake, BigQuery, Redshift, Databricks, and PostgreSQL. Data teams use it to run automated pipelines, handle schema mapping, monitor failures, and prepare content, product, and customer data for analytics. Its main fit is teams that need warehouse-ready data without writing and hosting a custom ingestion service for every source.

Why integrate Hevo Data with a headless CMS?

Content changes rarely stay inside one system. A product description update might need to show up on the website, feed a marketplace report, join with Shopify revenue in BigQuery, and appear in a Looker dashboard before tomorrow’s merchandising meeting. If your headless CMS and your data pipeline don’t talk to each other, someone usually exports CSVs, copies fields into spreadsheets, or waits for a nightly batch job that’s already stale by the time the team uses it.

Connecting Hevo Data to a headless CMS gives your analytics and operations teams a clean event stream from editorial work. Published articles, product detail pages, campaign landing pages, localization status, author metadata, and taxonomy changes can flow into the same warehouse where you already analyze traffic, orders, support tickets, and ad spend. Hevo Data can receive those events through its Webhook Source, infer or map the incoming JSON structure, and load the records into your destination.

Sanity works well as the source side because content in the Content Lake is typed JSON, not scraped HTML or page blobs. GROQ lets you fetch exactly the fields Hevo Data should receive, including joined reference data like author names, category labels, and product IDs. Webhooks trigger when content is published, updated, or deleted, and Functions can run the server-side sync logic without a separate worker service. The trade-off is that you still need to design event payloads carefully. If you rename fields or change schemas, treat the Hevo pipeline and warehouse tables like downstream contracts.

Architecture overview

A typical flow starts with a publish event in Sanity Studio. A Sanity webhook listens for specific mutations, for example published product, article, campaign, or localization documents. The webhook payload can include the document ID and type, then a Sanity Function or webhook handler uses @sanity/client and GROQ to fetch the current document from the Content Lake with only the fields Hevo Data needs. The sync layer then POSTs a JSON payload to the Hevo Data Webhook Source URL you copy from the Hevo dashboard. Hevo Data treats that webhook as a source, parses the JSON event, maps fields to the configured destination, and loads the data into your warehouse or database. From there, analysts, BI tools, reverse ETL jobs, and internal applications can query the content data alongside revenue, campaign, inventory, and customer data. Use webhooks when the transformation is light, like forwarding a normalized article event. Use Functions when you need server-side logic close to the content event, such as fetching referenced documents, removing draft IDs, mapping Sanity field names to warehouse column names, or sending delete tombstones to Hevo Data. In both cases, GROQ keeps the payload narrow, so you don’t send the entire document when Hevo Data only needs 12 fields.

Common use cases

Step-by-step integration

1. 1

   Create a Hevo Data Webhook Source

   In Hevo Data, create or open your workspace, add a Source, choose Webhook, name the source, connect it to a destination such as BigQuery, Snowflake, Redshift, or Databricks, and copy the generated Webhook URL. Hevo’s Webhook Source doesn’t require a Node SDK. The generated HTTPS URL is the ingestion API endpoint, so store it as a secret such as HEVO_WEBHOOK_URL.

2. 2

   Model the content in Sanity Studio

   Define the fields your data pipeline needs, not just the fields your page renders. For an article, that might include title, slug, publish date, author reference, category references, canonical URL, locale, campaign ID, and status. For products, include SKU, product family, merchandising labels, and references to reusable content blocks.

3. 3

   Create a publish webhook in Sanity

   In your Sanity project settings, add a webhook that triggers on create, update, and delete events for the document types you want to send to Hevo Data. Use a GROQ filter like _type in ["post", "product", "campaign"] && !(_id in path("drafts.**")) and include a small projection with _id, _type, and operation data.

4. 4

   Add a Sanity Function or webhook handler

   Use a Sanity Function, Next.js route, Express handler, or other server-side endpoint to receive the webhook. Fetch the latest document from the Content Lake with @sanity/client, select fields with GROQ, normalize the payload, and POST it to the Hevo Data Webhook Source URL.

5. 5

   Test the Hevo Data pipeline

   Publish one test document, confirm Hevo Data receives the event, review the inferred schema, and map fields to your destination table. Test an update and a delete too. For deletes, send a tombstone event with _id, _type, deleted: true, and deletedAt so your warehouse tables don’t keep stale records.

6. 6

   Build the reporting or frontend experience

   Once content events land in your destination, connect Looker, Tableau, Mode, dbt, reverse ETL, or an internal dashboard. Keep the website and app reading from Sanity while analytics and operations read from the warehouse tables populated by Hevo Data.

How Sanity + Hevo Data works

CMS approaches to Hevo Data

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