GraphQL API Development Services

When your mobile app needs a subset of what your web dashboard needs, a REST API that returns the same payload to both is doing unnecessary work on both ends.

GraphQL lets API consumers request exactly the data they need, no more, no less. A mobile app that needs a user's name and avatar doesn't receive the full user object. A dashboard that needs nested relationships gets them in a single request rather than multiple round trips. The client specifies the shape of the data and the API delivers it.
RaftLabs builds GraphQL APIs using Apollo Server and GraphQL Yoga for Node.js backends, with schema design, resolver implementation, DataLoader for N+1 query prevention, authentication and authorization at the resolver level, and schema documentation. For teams replacing a REST API that has become unwieldy to extend, or for new products with multiple client types that need different data shapes.

  • Schema design that models your business domain cleanly, types, queries, mutations, and subscriptions for real-time data

  • DataLoader implementation to prevent N+1 queries that make GraphQL slow in production

  • Field-level authorization so different client types see only the fields they're permitted to access

  • GraphQL Playground and schema introspection documentation that developers can use without reading separate docs

Recent outcomes

Voice AI · Research

6× deeper insights

Text-based interviews converted to automated phone calls

AI Automation · Ops

20k+ txns day one

Manual invoice OCR across 40+ gas stations

Loyalty · Retail

1,062 users in 4 weeks

SuperValu & Centra loyalty platform with receipt validation

SaaS · Logistics

2,000+ shipments yr 1

Multi-carrier shipping hub for Indonesian eCommerce

4.9
on Clutch
See our work

The problem

Sound familiar?

  • Are your REST API clients (mobile, web, partner) each receiving oversized payloads because the API was designed for the most data-hungry consumer and everyone else gets the excess?

  • Is adding a new field to your REST API responses causing breaking changes for clients that don't need the field?

Short answer

RaftLabs builds GraphQL APIs with Apollo Server or GraphQL Yoga: schema design, resolvers, DataLoader for N+1 prevention, field-level authorization, query-cost limiting, and real-time subscriptions for mobile, web, and partner clients that share one schema. A first single-domain GraphQL layer starts around $25,000 to $45,000 and grows to $60,000 to $130,000 for federation and subscriptions. A validated v1 ships in 6 to 14 weeks at a fixed cost.

Key takeaways

  • A first single-domain GraphQL layer with schema design, DataLoader, and field-level auth starts around $25,000 to $45,000, and grows to $60,000 to $130,000 as you add federation and subscriptions.
  • A validated v1 ships in 6 to 14 weeks at a fixed cost agreed before development starts, then iterates from there.
  • DataLoader implementation prevents N+1 queries, the most common GraphQL production performance failure.
  • Field-level authorization lets mobile, web, and partner clients share one schema while each sees only the fields their role permits.
  • GraphQL subscriptions over WebSocket push real-time updates to connected clients without polling.
  • Schema documentation via GraphQL Playground and introspection: developers can explore and test authenticated queries without separate docs.

Trusted by

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GraphQL solves a problem REST handles badly: several client types with different data requirements hitting one API surface. A mobile app might want three fields; a web dashboard wants thirty. A REST endpoint that returns all thirty over-serves the mobile app and makes it download payload it throws away. When a screen needs nested relationships, REST assembles them across several calls. One GraphQL query returns the exact shape the client asked for.

GraphQL earns its bad performance reputation only when teams skip the work that makes it fast in production. The N+1 problem is the usual culprit: each item in a list fires its own database call, so a list of 50 becomes 51 round trips. DataLoader batches those into one. Query-cost and depth limits stop a client from composing a query that quietly melts your database. We build all of this into every project, not as a later add-on.

Adoption backs the shift. GraphQL now reaches 33% of developers (Postman, 2025 State of the API Report), and Gartner projects more than 60% of enterprises will run it in production by 2027, up from under 30% in 2024 (Gartner, "When to Use GraphQL to Accelerate API Delivery," 2024). Almost all of them serve mobile, web, and partner clients that outgrew a single REST contract.

33%
of developers now use GraphQL
Postman, 2025 State of the API Report
60%+
of enterprises in production by 2027, up from under 30% in 2024
Gartner, 2024
51 to 2
database queries for 50 records with their authors, DataLoader on
N+1 batching, per request

Getting to production takes more than a schema. Persisted queries lock live clients to approved query hashes, and because those become plain GET requests, a CDN can cache them at the edge. Response caching keyed by type and id keeps hot objects off the database. We wire cost limiting, persisted queries, and caching in from the start, so the API holds its speed as query traffic grows.

Capabilities

What we build

  • 01
    GraphQL schema design

    Type definitions that model your business domain accurately rather than mirroring database tables: object types, inputs, enums, interfaces, and unions, plus queries, mutations, and subscriptions. Interface and union types handle polymorphic data in a single query, and Relay-compatible cursor pagination works natively. We review the schema before anyone writes a resolver: a naming problem caught in review takes minutes to fix, but becomes a breaking change once clients integrate.

    Built with
    Apollo Client · Relay · graphql-inspector
  • 02
    Resolver implementation

    Resolver functions for every field, with the resolver layer separated from the service layer so business logic can be tested independently and reused by REST endpoints or background jobs. Context injection provides database connections, the authenticated user, and DataLoader instances per request, errors return structured GraphQL codes with partial success, and Apollo Server plugins add request tracing and slow-field detection.

    Built with
    Apollo Server · Prisma · TypeORM · Knex
  • 03
    N+1 query prevention with DataLoader

    DataLoader implementation for every resolver that fetches related data, batching database calls within a single request. The N+1 problem is GraphQL's most common production failure: 50 articles with their authors means 51 queries without DataLoader, 2 with it. Instances are scoped per request, query complexity analysis and depth limiting reject queries that would generate unbounded database load, and persisted queries lock production clients to approved query hashes.

    Built with
    DataLoader · Persisted queries
  • 04
    Authentication and field-level authorization

    JWT or session authentication validated in GraphQL context before any resolver runs, so a failed check short-circuits the whole request. Field-level authorization with graphql-shield or custom directives lets public, partner, and admin clients share one schema while each sees only the fields their role permits. RBAC and ABAC patterns live at the resolver layer, and an unauthorized field returns a structured FORBIDDEN error for that field alone.

    Built with
    JWT · graphql-shield · RBAC · ABAC
  • 05
    GraphQL subscriptions for real-time data

    Subscription implementation for real-time data over WebSocket, pushing updates to connected clients instead of forcing them to poll. Built on Apollo Server with graphql-ws, authentication is validated during the WebSocket handshake, Redis-backed PubSub shares subscription events across server instances, and events filter server-side per subscription so a client watching one order receives only that order's updates.

    Built with
    Apollo Server · graphql-ws · WebSocket · Redis PubSub
  • 06
    Schema documentation and federation

    GraphQL Playground and Apollo Sandbox for interactive schema exploration, with auth headers configured so developers test authenticated queries in the docs. Documentation lives as SDL descriptions in the schema itself, served via introspection, so it never drifts from the implementation, and Apollo Federation 2 composes multiple GraphQL services into one unified graph behind an Apollo Router gateway. Versioning uses @deprecated annotations for additive changes.

    Built with
    GraphQL Playground · Apollo Sandbox · Apollo Federation 2 · Apollo Router

Have a GraphQL project?

Tell us your client types, the data relationships that are difficult to express in your current API, and what you're trying to solve. We'll scope it and give you a fixed cost.

What clients say

What our clients say

Three-year average engagement. Founders and operators describing the work in their own words. No marketing varnish.

Charles E.
Charles E.
USA flagUSA
Entrepreneur at Aggie Technologies

All of the sprints were completed on schedule and on budget. We highly recommend RaftLabs!

01 / 02

Stay on topic

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Frequently asked questions

GraphQL is the better choice when you have multiple client types with different data requirements (mobile, web, third-party) that would benefit from fetching exactly what they need; when your data has complex relationships that require multiple REST round trips to assemble; or when your schema evolves frequently and you want to add fields without versioning the API. REST is simpler when your clients have uniform data requirements, when your team is not familiar with GraphQL tooling, or when you have simple CRUD operations without complex relationships. Both are valid, the choice follows your client diversity and schema complexity.

Query complexity analysis assigns a cost to each field in the query and rejects queries whose total cost exceeds a configured limit. Depth limiting rejects queries that nest beyond a maximum depth. Both are implemented at the server level before resolvers execute. Persisted queries, where production clients only send a query hash rather than the full query text, prevent arbitrary query construction entirely, and are the most effective defense for production APIs where the client code is controlled.

Yes. Many production APIs serve a GraphQL endpoint for flexible client queries alongside REST endpoints for specific use cases: webhooks (which are inherently REST callbacks), file uploads (which REST handles more naturally than GraphQL multipart), and integrations with third-party systems that expect REST. A common pattern is a GraphQL endpoint for frontend clients alongside REST endpoints for partner integrations and internal service-to-service calls. The two don't need to be an either-or decision.

Both compose several GraphQL services into one graph, but they split the work differently. Schema stitching merges schemas at a gateway where you hand-write the type merging and conflict resolution, so the gateway holds the composition logic and every change ripples back to it. Apollo Federation moves ownership to the subgraphs: each service declares the types it owns and how they connect through directives, and the router composes the supergraph from that. For a handful of stable services, stitching is fine. For many teams shipping independently, federation scales better because no single gateway file becomes the bottleneck. We default to Federation 2 for new multi-service graphs.

A first GraphQL layer over a single domain, with schema design, resolvers, DataLoader, and field-level authorization, starts around $25,000 to $45,000. As you add subscriptions, federation across services, and a query-cost and depth-limiting layer, it grows to $60,000 to $130,000. You get a fixed cost agreed before development starts.

Work with us

Tell us what you need. We'll tell you what it would take.

We scope GraphQL API Development in 30 minutes. You walk away with a clear cost, timeline, and approach. No commitment required.

  • Scope and cost agreed before work starts. No surprises. No obligation.
  • Working prototype within 3 weeks of kickoff.
  • Pay by milestone. You see progress before each invoice.
  • 60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
  • All conversations are NDA-protected.