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GraphQL vs PostGraphile: What are the differences?
GraphQL: A data query language and runtime. 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; PostGraphile: Instant GraphQL API for your PostgreSQL database; use standalone or as a Node.js middleware; MIT-licensed OSS. Execute one command (or mount one Node.js middleware) and get an instant high-performance GraphQL API for your PostgreSQL database.
GraphQL and PostGraphile belong to "Query Languages" category of the tech stack.
Some of the features offered by GraphQL are:
- Hierarchical
- Product-centric
- Client-specified queries
On the other hand, PostGraphile provides the following key features:
- instant GraphQL schema via reflection over PostgreSQL database API
- compiles complex GraphQL queries into very few SQL statements resulting in high performance
- built entirely from plugins - heavily customisable
GraphQL and PostGraphile are both open source tools. GraphQL with 11.7K GitHub stars and 753 forks on GitHub appears to be more popular than PostGraphile with 7.49K GitHub stars and 364 GitHub forks.
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Learn MorePros of GraphQL
Pros of PostGraphile
Pros of GraphQL
- Schemas defined by the requests made by the user74
- Will replace RESTful interfaces62
- The future of API's60
- The future of databases48
- Self-documenting12
- Get many resources in a single request11
- Query Language5
- Ask for what you need, get exactly that5
- Fetch different resources in one request3
- Evolve your API without versions3
- Type system3
- Easy setup2
- GraphiQL2
- Ease of client creation2
- Good for apps that query at build time. (SSR/Gatsby)1
- Backed by Facebook1
- Easy to learn1
- "Open" document1
- Better versioning1
- Standard1
- 1. Describe your data1
- Fast prototyping1
Pros of PostGraphile
- Postgres based authentication10
- Great developer support6
- Lightning fast5
- Database first with no braking changes5
- Simple to set up and scale4
- Bye bye Resolvers4
- Back to database first3
- 9 Automatically generates your GraphQL schema3
- Easy setup of relationships and permissions3
- Instant production ready GraphQL3
- Works with new and existing databases1
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Cons of GraphQL
Cons of PostGraphile
Cons of GraphQL
- Hard to migrate from GraphQL to another technology4
- More code to type.4
- Takes longer to build compared to schemaless.2
- All the pros sound like NFT pitches1
- Works just like any other API at runtime1
Cons of PostGraphile
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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 PostGraphile?
Execute one command (or mount one Node.js middleware) and get an instant high-performance GraphQL API for your PostgreSQL database
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Jobs that mention GraphQL and PostGraphile as a desired skillset
What companies use GraphQL?
What companies use PostGraphile?
What companies use GraphQL?
What companies use PostGraphile?
See which teams inside your own company are using GraphQL or PostGraphile.
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What tools integrate with GraphQL?
What tools integrate with PostGraphile?
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What are some alternatives to GraphQL and PostGraphile?
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.