GraphQL development company
We design GraphQL schemas around how your clients actually read data, then build the resolvers, caching, security limits and federation needed to keep one graph fast and safe as more teams and more frontends depend on it.
- Senior engineers · IST + EST overlap
- NDA on day 1
- 24-hour reply
- Projects shipped
- 50+
- Code ownership
- 100%
- Client rating
- 4.8/5
- First reply
- 24h
GraphQL development company for schema-first APIs
Krapton is a GraphQL development company that designs and builds GraphQL APIs, from a single server in front of your database to a federated supergraph spanning many services. GraphQL lets each client ask for exactly the fields it needs through one typed endpoint, which suits products with web, mobile and partner clients that read the same data differently. The flexibility moves cost to the server. Naive resolvers fire one database query per item in a list (the N+1 problem), deeply nested or aliased queries can exhaust resources, and caching is harder than with REST because most requests are POSTs to a single URL. Our engineers address each deliberately: DataLoader batching per request, depth and cost limits with tools like GraphQL Armor, persisted or trusted documents so production accepts only known operations, and response caching where data allows. We write schemas in SDL or code-first with Pothos or NestJS, generate TypeScript types with GraphQL Code Generator, and check every schema change for breaking edits before it ships.
GraphQL development services
Schema design and governance
Domain-driven type design, nullability decisions, Relay-style cursor pagination, input and error conventions, and deprecation rules, reviewed with your frontend teams and enforced by graphql-eslint and schema checks in CI.
GraphQL server development
Production servers on Apollo Server, GraphQL Yoga or Mercurius for Node.js, Strawberry for Python, gqlgen for Go, or Netflix DGS for Java, with resolvers batched through DataLoader or its equivalent.
Federation and supergraphs
Splitting a monolithic schema into Apollo Federation subgraphs owned by separate teams, composed and served through Apollo Router, Hive Gateway or WunderGraph Cosmo, with composition checks before each deploy.
REST-to-GraphQL layer
A GraphQL gateway over existing REST services and databases, so new clients get a typed graph while legacy endpoints keep running and are retired at your pace.
Client integration and caching
Apollo Client, urql or Relay setups with normalized caches, fragment colocation, optimistic updates and typed hooks from GraphQL Code Generator for React, React Native and other frontends.
Subscriptions and real-time data
Live updates over the graphql-ws protocol or server-sent events, backed by Redis or Kafka pub/sub so subscriptions keep working when the server runs on several instances.
Why teams choose Krapton for GraphQL
Senior engineers, fixed scope, and code you own — the things agencies promise and rarely deliver.
Performance designed into resolvers
We trace resolver timings with OpenTelemetry or Apollo usage reporting, batch and cache data access, and set cost limits from real operation shapes rather than guesses.
Authorization at the field
Access rules live in the business layer and are applied per field and per object, so a nested query cannot reach data that the top-level check would have blocked.
Schema changes without breakage
Every pull request runs a schema diff against operations clients actually send, so removing or retyping a field in use fails CI instead of breaking a mobile release.
Honest about when not to
If a single web client consumes simple CRUD, Krapton may recommend REST or tRPC instead, because GraphQL adds a schema layer, tooling and security work you then maintain.
How a GraphQL project runs with Krapton
01
Operation inventory
We list the screens and integrations that will query the graph, collect the data each one needs, and let those operations shape the schema.
02
Schema review
A draft schema is reviewed with frontend and backend owners, covering naming, nullability, pagination and errors, before any resolver code is written.
03
Resolvers and protection
Resolvers, DataLoaders, authorization and cost limits are built and load-tested with realistic nested queries, including hostile ones designed to exhaust the server.
04
Launch and evolve
We enable persisted operations, monitoring per operation name and a deprecation workflow, so the graph keeps evolving after launch without surprise breakages.
The GraphQL stack we build with
GraphQL development: questions answered
What should I expect from a GraphQL development company?
Expect schema design first and code second. A capable team starts from the operations your clients will run, designs types, pagination and errors around them, then builds resolvers with batching, authorization and query limits. Krapton also sets up type generation for your frontends, schema checks in CI, and per-operation monitoring, so the graph stays maintainable after the initial build.
Is GraphQL better than REST for our API?
It depends on your clients more than your backend. GraphQL pays off when several frontends need different slices of related data, when mobile apps suffer from over-fetching, or when many teams contribute to one API. REST stays simpler for public APIs that benefit from HTTP caching, file-heavy endpoints, and small services with one consumer. Many systems run both.
How do you migrate from REST to GraphQL without a rewrite?
We put GraphQL in front of what you already have. Resolvers call your existing REST endpoints or services, using DataLoader to batch and deduplicate requests, so clients can adopt the graph screen by screen. Once traffic has moved, heavy resolvers can be rewired to read the database directly, and unused REST routes are retired.
How do you secure a GraphQL API against abusive queries?
We limit what a query can cost before executing it. Depth limits, alias and batch limits, and cost analysis reject expensive operations, while persisted or trusted documents let production accept only queries your own clients registered. Introspection is usually disabled for private APIs, rate limits apply per client, and authorization runs in resolvers or the business layer, never only at the gateway.
What shapes the cost of GraphQL development services?
The number and complexity of underlying data sources shape it most. A graph over one well-modeled database is far simpler than one stitching together legacy REST services, third-party APIs and several databases. Federation across teams, real-time subscriptions, fine-grained authorization rules, client migration work and performance targets add further effort, as does the governance tooling you want around schema changes.
Ready to build? Tell us what you have in mind.
Send a short brief and a senior engineer will reply within one business day with next steps — no sales fluff.