Top 5 Strategies for Migrating From Drupal to a Headless CMS

Your Drupal 7 site went end of life on January 5, 2025, and the "upgrade" your team keeps deferring is not an upgrade at all. Moving to Drupal 10 or 11 is a rebuild-and-migrate project, not an in-place bump, so the moment you accept you have to rebuild anyway, the harder question surfaces: rebuild on Drupal, or leave the node, field, and entity model behind entirely? Sanity is one of the destinations teams shortlist when they decide the answer is "leave it behind." It is the Content Operating System for the AI era, the intelligent backend for teams that want structured, queryable content instead of Drupal render output stitched together at theme time.

This is a Top 5 ranking of where Drupal teams actually land, ordered by how much of the re-platform problem each option resolves versus defers. The mechanics are the same everywhere: inventory your content, map URLs and fields, translate nodes and taxonomy terms into a JSON model, restructure rich text, and handle assets separately. What differs is what the content model, the editor, and the query layer look like after you land, and whether the hosting-and-update burden that pushed you off Drupal 7 comes along for the ride.

1. Sanity: leave the node model behind, land on structured content

The highest-leverage move is the one that resolves the re-platform pressure instead of deferring it. On Sanity you define your content model in code with defineType, and TypeGen turns those schemas into TypeScript, so the shape of a Drupal article node becomes a versioned, reviewable artifact in your repo rather than a stack of field configuration in a database. Content Lake stores everything as JSON and decouples structure from storage, which is exactly the property that makes a migration auditable: you import, then refactor.

The mechanics map cleanly onto a Drupal cutover. The Content Lake migrations API lets you write scripts that operate on node values inside documents, use GROQ filters to select what to change, and traverse and transform nested fields with node and path-based mutation helpers. The part every Drupal migration stalls on, what happens to the body field, has a documented answer: HTML and rich text convert to Portable Text using the @portabletext/block-tools package inside a Node-based bulk-import script. Your body blobs become structured, queryable content with real marks and annotations, not HTML you re-parse forever.

After import, you validate with GROQ instead of SQL joins against the old database. GROQ projections return exactly the shape the frontend needs in one round trip, including references and filters, so a migrated taxonomy relationship resolves in the query rather than in three follow-up calls. Where it fits poorly: if you genuinely want to keep Drupal's editors and workflows untouched and change nothing, this is more work than a decouple. That work is the point; you are cashing out the rebuild you already have to do.

2. Decoupled (headless) Drupal: lowest migration cost, deferred reckoning

If the calendar is the only forcing function and the content model is fine, the pragmatic answer is to decouple Drupal in place. You keep Drupal as a content API behind JSON:API or GraphQL and put a React, Vue, or Next.js frontend on it. The content stays put, the editors keep the interface they know, and you get a modern frontend without a full data migration. For a team under deadline pressure with a healthy editorial workflow, this is genuinely the lowest-risk path, and it aligns with the incremental-decoupling guidance: keep the existing site online, start with a proof of concept, migrate critical templates first, and avoid a big-bang cutover.

What it does well is precisely what it does not resolve. You still carry Drupal's node, field, and entity model, its render and theming assumptions, and its hosting and update burden. Rich text is still Drupal's rendered output, so the frontend consumes HTML rather than structured, queryable content, and your team keeps maintaining Drupal core, contrib modules, and the security update cadence that pushed you off Drupal 7 in the first place.

The concrete failure mode shows up eighteen months later. Drupal 10 goes end of life, Drupal 11 lands, and the rebuild-and-migrate project you avoided is back on the roadmap, now with a React frontend coupled to a JSON:API contract you also have to version. Decoupled Drupal is the right call when the content model is sound and you need a frontend refresh, not a platform change. It is the wrong call if you chose Drupal 7 EOL as the moment to stop maintaining a CMS runtime at all, because that reckoning is only postponed.

3. Contentful: managed API-first landing spot with a fixed editor

Contentful is a frequent "where do we land" shortlist option for teams leaving Drupal, and for good reason. It is a mature, API-first headless CMS with a managed content delivery API, Live Preview, and a large ecosystem, so you get off Drupal's hosting-and-update treadmill and onto a SaaS backend without running infrastructure. For a Drupal team whose primary pain is operational burden rather than modeling flexibility, that trade is attractive on day one.

Where it fits the migration well: content types map reasonably onto Drupal node types, references cover taxonomy relationships, and the delivery API removes the render-layer coupling that decoupled Drupal leaves behind. Where the fit gets tighter is the editor and the model. Schema is defined and managed through the platform GUI or CLI, with definitions tied to stored content, so structural changes are a platform operation rather than a code review in your repo. The editorial UI is a fixed layout extended through UI extensions, so when a migrated Drupal workflow needs a bespoke editing surface, you are configuring extension points rather than shipping an editor as code the way you would with Sanity Studio.

A concrete example: your Drupal body field carried inline components and custom callouts. In Contentful you model those as linked entries or rich-text embedded blocks and wire UI extensions to edit them. It works. The difference from Sanity is that on Sanity the equivalent lands as Portable Text with custom marks and annotations, and the input to edit it is a custom React component you version in sanity.config.ts. Both migrate the content; they differ in whether the editor and schema live in the platform or in your codebase.

4. WordPress headless (WPGraphQL): familiar, but the rich text problem survives

WordPress headless is the common alternative landing spot for teams leaving Drupal, usually because the organization already knows WordPress or wants the lower editorial learning curve. With WPGraphQL and the REST API you get real headless capability: a GraphQL endpoint over posts, pages, custom post types, and Advanced Custom Fields, consumed by a Next.js or Astro frontend. For a content team whose Drupal site was mostly articles and landing pages, the WordPress model feels close enough to be an easy sell internally.

What it does well is breadth and familiarity. The plugin ecosystem is enormous, editors are comfortable, and WPGraphQL exposes a serviceable API for a decoupled frontend. Where it fits poorly is the same structural weakness Drupal had: the content model is still page and post plus custom fields bolted on, and rich text stays as HTML blobs rather than structured, queryable content. You migrate off Drupal and inherit a different flavor of the exact problem, your body content is markup you parse on the frontend, not data you query.

The concrete example is the migrated article body. In Drupal it was rendered HTML; in WordPress headless it is still HTML, now delivered over GraphQL. If a redesign needs to pull every pull-quote across the archive, or feed clean structured text to a downstream system, you are writing HTML parsers against post_content. On Sanity that same body is Portable Text, and a GROQ projection returns the blocks you want directly. WordPress headless is a reasonable destination when familiarity outranks modeling, and a poor one if the reason you are leaving Drupal is that unstructured rich text has become a maintenance tax you want gone.

5. Homegrown headless: a Drupal export plus a search index you now own

The fifth pattern is not a product, it is the temptation to build. A team confident in its stack exports Drupal content to a database or object store, stands up its own API, and wires a search index for retrieval. For a small, well-defined site with strong engineering it can work, and it gives you total control over the model and the query surface. It ranks last here not because it cannot be done but because it converts a one-time migration into a permanent operational commitment, which is the opposite of why most teams leave Drupal.

The cost lands after launch. What every homegrown retrieval setup requires, and what Content Lake handles for you, is a content pipeline that keeps the search index fresh. When a product description updates, a price changes, an article publishes, or a record is deleted, the index has to know. Building that yourself, incremental indexing, re-embedding on change, deletion handling, eventual-consistency reasoning, and backfill for schema changes, is a real project and a class of bug all its own. On Content Lake the index stays fresh automatically on publish, update, and delete, so the freshness problem stops being something the team maintains.

There is a capability angle too. Once content lands as structured data, GROQ composes hard filtering with keyword and semantic ranking in a single query, for example score(boost([title] match text::query($queryText), 2), text::semanticSimilarity($queryText)). Pure structured query is precise but falls over the moment someone searches "the cozy one" in vibes rather than fields; blended ranking covers both. Reproducing that on a homegrown stack means owning an embedding pipeline and a ranking layer forever. The homegrown route is defensible for a team that truly wants to own the whole thing; for everyone else it recreates the maintenance burden they migrated to escape.