When Gatsby Doesn't Suck in 2025

So we're rebuilding our company's documentation site. Three different content sources: Contentful for marketing pages, WordPress for the blog, and our internal API for product specs. The project manager wants everything looking unified - same navigation, same search, same everything.

First instinct was Next.js. Set up API routes to fetch from each source, build some shared components, call it a day. Except content comes from three different schemas, the blog uses WordPress's weird category structure, and the product specs change every week when engineering updates the API.

Three weeks into development, I had custom loading states for each content type, three different error handling patterns, and a caching strategy held together with duct tape and prayer. Every time someone added a new content field, I had to update the API route, the TypeScript interfaces, and the frontend components. Pure fucking hell.

Manager suggests trying Gatsby since the CIA website apparently uses it for similar multi-source content. Figured I'd waste a few days proving it wouldn't work, then get approval to rebuild everything in Next.js properly.

Turned out Gatsby's GraphQL layer actually handles this exact nightmare scenario. Write your sources once:

// gatsby-config.js
plugins: [
  'gatsby-source-contentful',
  'gatsby-source-wordpress', 
  'gatsby-source-custom-api'
]

Then query everything through one interface. All your data shows up in GraphiQL, relationships get created automatically, and you get one fucking query instead of three API calls with separate error handling.

When Your React Team Doesn't Want to Learn Yet Another Thing

Our frontend team knows React, Apollo Client, and TypeScript. That's it. They're good at those tools, but asking them to learn Astro's component syntax or Hugo's Go templates means weeks of ramping up.

With Gatsby, they write the same React components they've been writing for years. Same hooks, same component composition, same context patterns. The only new thing is GraphQL queries, and if your team already uses Apollo, that's not even new.

TypeScript docs switched to Gatsby specifically because their contributor base didn't want to learn a different framework. Airbnb Design did the same thing. When experienced React developers can be productive on day one without reading documentation, that's worth something.

The Plugin Ecosystem Actually Works (Unlike Most Frameworks)

Gatsby has 2,000+ plugins and most of them actually work together without breaking everything. The image plugin (gatsby-plugin-image) automatically handles responsive images, lazy loading, WebP conversion, and blur placeholders. No configuration hell, no CDN setup nightmares.

Try doing the same thing in Next.js and you'll spend a day configuring next/image, setting up CloudFront, and debugging why your responsive images look like shit on mobile:

// Gatsby: Automatic responsive images from GraphQL
<GatsbyImage image={data.image.childImageSharp.gatsbyImageData} />

// Next.js: Manual configuration required
<Image 
  src=\"/image.jpg\" 
  width={800} 
  height={600}
  srcSet=\"...\" // Manual responsive variants
/>

The Gatsby plugin library has mature solutions for SEO, PWA stuff, analytics, and CMS connections that don't fuck with each other. Next.js can do the same things but good luck spending 3 days configuring dependencies that inevitably conflict.

When You Need Lighthouse Scores That Don't Suck

Gatsby generates static HTML with inline CSS and no render-blocking bullshit. Sourcegraph's docs get perfect Lighthouse scores without any performance optimization work. That's not marketing - that's just what happens when you pre-render everything.

Here's what you get out of the box:

• Critical CSS inlining: Above-the-fold styles load immediately (no FOUC)
• Code splitting: Each page loads only the JS it needs
• Prefetching: Next page resources load in background while user reads
• Image optimization: Automatic WebP, resizing, compression - all handled

Try implementing all that manually in other frameworks. Web.dev performance guides keep using Gatsby sites as examples of how to do performance right because it's actually hard to fuck up.

The One Time 47-Minute Builds Didn't Ruin My Life

So our marketing site at my last company updated maybe twice a month. New blog posts, product announcements, that kind of shit. The CEO would request changes on Friday at 5pm and expect them live Monday morning. Perfect use case for slow builds, right?

Wrong. First time our copywriter Sarah needed to fix a typo on the pricing page, she pushed to main at 2:30pm expecting a quick fix. Forty-seven fucking minutes later, the build was still running when the customer demo started at 3:00. Had to explain to prospects why our pricing page still said "Entreprise" instead of "Enterprise" during the product walkthrough. Sarah never used git push without asking me first after that.

But here's the thing - for purely marketing sites that genuinely update monthly, Gatsby's build time stops mattering. Our company blog got maybe 2 posts per month. WordPress would've been overkill with PHP version updates and security patches every week. Static files on Netlify just sit there working without maintenance.

The Figma blog probably rebuilds once a week for new posts. Nobody at Figma is sitting around waiting for builds to finish so they can preview a comma change. That's the only scenario where Gatsby's slowness doesn't actively hurt productivity.

Production Actually Works (Development Is Hell)

Production Gatsby sites are bulletproof once they're built. The React docs serve millions of developers without downtime, Apollo's GraphQL blog handles traffic spikes during conference announcements, Airbnb Design has been rock solid for years.

Static HTML and CSS files don't crash. No server memory leaks, no database timeouts, no Node.js processes dying unexpectedly. Put it on CloudFlare or AWS CloudFront and forget about it.

Meanwhile, development mode is a nightmare. gatsby develop starts at 400MB RAM and climbs to 3GB after an hour of hot reloading. My MacBook Pro fans spin up just opening the project. Hot reload breaks randomly and requires full restarts. The GraphiQL interface crashes if you query too much data at once.

But once it's built? Rock solid. The Figma blog hasn't gone down in years. Hosting costs are basically nothing - entire sites run on $5/month Netlify plans while your Next.js app needs a $50/month Vercel plan to handle traffic spikes. No server crashes, no database timeouts, no surprise AWS bills when your article hits the front page of Hacker News.

Production Sites That Actually Work

CIA.gov: Government-Scale Content Management

The CIA's official website demonstrates Gatsby handling enterprise requirements. With 3,000+ pages spanning multiple content types, security clearance levels, and data sources, they needed a framework that could unify complex content without compromising performance. The U.S. Digital Service and 18F have documented similar government website requirements for performance and accessibility. Their case studies show how government sites benefit from static generation approaches like JAMstack architectures.

Their implementation uses Gatsby's data layer to combine:

• Classified document metadata (sanitized for public view)
• Press releases from multiple government agencies
• Historical archives in different formats
• Multi-language content for international audiences

The result: sub-1-second page loads for a site serving millions of monthly visitors. Try achieving that with WordPress or Drupal handling government-scale content requirements.

Documentation Sites: TypeScript, React, Apollo

TypeScript's documentation rebuilt with Gatsby in 2022 and hasn't looked back. Similar to how Jest and Prettier handle their docs, TypeScript needed a solution that could handle complex technical content. The previous Next.js implementation struggled with:

• Cross-referencing between API docs and guides
• Generating multiple output formats from the same source
• Managing versioned documentation across TypeScript releases

Gatsby's GraphQL layer automatically creates relationships between code examples, API references, and explanatory text. Contributors write in MDX, and the build process generates searchable, interconnected documentation.

Similarly, Apollo GraphQL uses Gatsby for their developer blog because it integrates seamlessly with their existing GraphQL tooling. The irony isn't lost—the GraphQL company chose the GraphQL-native static site generator. Other GraphQL-heavy projects like Hasura and Dgraph followed similar patterns. The GraphQL Foundation itself uses static site tooling for their documentation.

Performance Patterns That Actually Work

Image-Heavy Content Sites

Airbnb Design showcases Gatsby's automatic image optimization. Their design system documentation includes hundreds of component screenshots, before/after comparisons, and high-resolution mockups.

With gatsby-plugin-image, every image automatically gets:

• WebP conversion with JPEG fallbacks
• Responsive variants for different screen sizes
• Lazy loading with blur placeholders
• Critical image prioritization for above-fold content

The manual equivalent in Next.js requires configuring next/image, setting up CloudFront distributions, and writing custom responsive image logic. Gatsby handles this complexity transparently.

Multi-Source Content Aggregation

News sites and content aggregators benefit from Gatsby's unified data layer. A typical implementation pulls from:

• Headless CMS for editorial content (Contentful, Strapi)
• Social media APIs for embedded content (Twitter, Instagram)
• Analytics APIs for trending/popular content
• E-commerce APIs for product information

The GraphQL schema automatically creates relationships between these sources. A product review can reference the product data, author information, and related social media discussions in a single query.

Compare this to Next.js where each data source requires separate API routes, caching strategies, and error handling. The complexity multiplies with each additional source.

Plugin Ecosystem Advantages

SEO and Analytics Integration

Gatsby's plugin ecosystem provides battle-tested solutions for common requirements:

• gatsby-plugin-google-gtag: Google Analytics 4 integration with GDPR compliance
• gatsby-plugin-sitemap: Automatic XML sitemaps with dynamic content
• gatsby-plugin-robots-txt: Robots.txt generation based on environment
• gatsby-plugin-schema-snapshot: Schema validation for large sites

These plugins work together without conflicts. The equivalent Next.js setup requires manual integration, testing for compatibility issues, and ongoing maintenance as APIs change.

Performance Monitoring

Production Gatsby sites integrate with performance monitoring tools seamlessly:

• gatsby-plugin-webpack-bundle-analyser: Bundle size tracking
• gatsby-plugin-offline: Service worker caching strategies
• gatsby-plugin-preact: Smaller runtime for performance-critical sites
• gatsby-plugin-csp: Content Security Policy headers

The plugin architecture ensures these optimizations don't interfere with each other. Next.js achieves similar results but requires more configuration and potential conflicts between optimization approaches.

Development Workflow Advantages

Content Creator Experience

Non-technical team members work better with Gatsby's content workflows:

1. Preview environments: Gatsby Cloud provides branch-based previews for content review
2. Build notifications: Slack/email alerts when content publishing completes
3. Error handling: Clear build failures when content structure changes
4. Content relationships: GraphQL automatically validates links between content

This matters for teams where marketing, design, and development collaborate on content. The structured approach prevents content errors that break production sites.

Developer Experience for React Teams

Teams already using React, GraphQL, and modern tooling find Gatsby familiar:

• Component development matches React patterns exactly
• GraphQL queries work like Apollo Client or Relay
• Build process integrates with existing CI/CD pipelines
• Deployment targets are static files (no server requirements)

The learning curve for experienced React developers is minimal. Compare this to Hugo (Go templates), Jekyll (Liquid), or Astro (new component syntax) where existing React knowledge doesn't transfer.

When Good Gatsby Goes Bad

Even in ideal scenarios, Gatsby sites hit performance walls. The GraphQL data layer that makes development pleasant becomes a memory-hungry monster at scale. Your perfectly architected content structure starts timing out during builds when you hit 5,000+ pages.

If your Gatsby site is showing stress fractures - longer build times, memory errors, or random failures - the next section covers the optimization techniques that can buy you more time before migration becomes unavoidable.