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GraphQL vs GraphQL Ruby: What are the differences?
- Syntax Differences: GraphQL Ruby uses Ruby syntax, which might be more familiar to Ruby developers, while GraphQL has its own specific query syntax that might require a learning curve for developers new to it.
- Type System Differences: GraphQL Ruby uses Ruby's type system, which is statically typed, while GraphQL has its own type system that allows for efficient data querying and manipulation.
- Execution Differences: GraphQL Ruby executes queries using Ruby's execution environment, while GraphQL has a dedicated runtime for executing queries efficiently.
- Error Handling Differences: GraphQL Ruby has error handling mechanisms specific to Ruby, while GraphQL provides a standardized error handling mechanism for all its implementations.
- Community Support Differences: GraphQL has a larger community and ecosystem with extensive resources and tools available for developers, while GraphQL Ruby may have a more specialized community focus due to its specific implementation in Ruby.
- Performance Differences: Due to the runtime optimizations of GraphQL, it may offer better performance in query execution compared to GraphQL Ruby which relies on Ruby's execution environment.
In Summary, key differences between GraphQL and GraphQL Ruby encompass syntax, type system, execution, error handling, community support, and performance.
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Learn MorePros of GraphQL
Pros of GraphQL Ruby
Pros of GraphQL
- Schemas defined by the requests made by the user75
- Will replace RESTful interfaces63
- The future of API's62
- The future of databases49
- Self-documenting13
- Get many resources in a single request12
- Query Language6
- Ask for what you need, get exactly that6
- Fetch different resources in one request3
- Type system3
- Evolve your API without versions3
- Ease of client creation2
- GraphiQL2
- Easy setup2
- "Open" document1
- Fast prototyping1
- Supports subscription1
- Standard1
- Good for apps that query at build time. (SSR/Gatsby)1
- 1. Describe your data1
- Better versioning1
- Backed by Facebook1
- Easy to learn1
Pros of GraphQL Ruby
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Cons of GraphQL
Cons of GraphQL Ruby
Cons of GraphQL
- Hard to migrate from GraphQL to another technology4
- More code to type.4
- Takes longer to build compared to schemaless.2
- No support for caching1
- All the pros sound like NFT pitches1
- No support for streaming1
- Works just like any other API at runtime1
- N+1 fetch problem1
- No built in security1
Cons of GraphQL Ruby
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- No public GitHub repository available -
What is GraphQL?
GraphQL is a data query language and runtime designed and used at Facebook to request and deliver data to mobile and web apps since 2012.
What is GraphQL Ruby?
Get going fast with the graphql gem, battle-tested and trusted by GitHub and Shopify.
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Jobs that mention GraphQL and GraphQL Ruby as a desired skillset
What companies use GraphQL?
What companies use GraphQL Ruby?
What companies use GraphQL?
What companies use GraphQL Ruby?
See which teams inside your own company are using GraphQL or GraphQL Ruby.
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What tools integrate with GraphQL?
What tools integrate with GraphQL Ruby?
What tools integrate with GraphQL Ruby?
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What are some alternatives to GraphQL and GraphQL Ruby?
gRPC
gRPC is a modern open source high performance RPC framework that can run in any environment. It can efficiently connect services in and across data centers with pluggable support for load balancing, tracing, health checking...
Falcor
Falcor lets you represent all your remote data sources as a single domain model via a virtual JSON graph. You code the same way no matter where the data is, whether in memory on the client or over the network on the server.
React
Lots of people use React as the V in MVC. Since React makes no assumptions about the rest of your technology stack, it's easy to try it out on a small feature in an existing project.
graphql.js
Lightest GraphQL client with intelligent features. You can download graphql.js directly, or you can use Bower or NPM.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.