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Dgraph

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GraphQL

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298
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Dgraph vs GraphQL: What are the differences?

Dgraph: Fast, Distributed Graph DB. Dgraph's goal is to provide Google production level scale and throughput, with low enough latency to be serving real time user queries, over terabytes of structured data. Dgraph supports GraphQL-like query syntax, and responds in JSON and Protocol Buffers over GRPC and HTTP; 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.

Dgraph belongs to "Graph Databases" category of the tech stack, while GraphQL can be primarily classified under "Query Languages".

Dgraph and GraphQL are both open source tools. It seems that GraphQL with 11.8K GitHub stars and 769 forks on GitHub has more adoption than Dgraph with 10.4K GitHub stars and 716 GitHub forks.

Facebook, Instagram, and Twitter are some of the popular companies that use GraphQL, whereas Dgraph is used by Dgraph Labs, Inflect, and DealTap. GraphQL has a broader approval, being mentioned in 777 company stacks & 3271 developers stacks; compared to Dgraph, which is listed in 9 company stacks and 10 developer stacks.

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Pros of Dgraph
Pros of GraphQL
  • 3
    Graphql as a query language is nice if you like apollo
  • 2
    Easy set up
  • 2
    Low learning curve
  • 1
    Open Source
  • 1
    High Performance
  • 73
    Schemas defined by the requests made by the user
  • 62
    Will replace RESTful interfaces
  • 60
    The future of API's
  • 48
    The future of databases
  • 12
    Self-documenting
  • 11
    Get many resources in a single request
  • 5
    Ask for what you need, get exactly that
  • 4
    Query Language
  • 3
    Evolve your API without versions
  • 3
    Fetch different resources in one request
  • 3
    Type system
  • 2
    GraphiQL
  • 2
    Ease of client creation
  • 2
    Easy setup
  • 1
    Good for apps that query at build time. (SSR/Gatsby)
  • 1
    Backed by Facebook
  • 1
    Easy to learn
  • 1
    "Open" document
  • 1
    Better versioning
  • 1
    Standard
  • 1
    1. Describe your data
  • 1
    Fast prototyping

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Cons of Dgraph
Cons of GraphQL
    Be the first to leave a con
    • 3
      Hard to migrate from GraphQL to another technology
    • 3
      More code to type.
    • 1
      All the pros sound like NFT pitches
    • 1
      Works just like any other API at runtime
    • 1
      Takes longer to build compared to schemaless.

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    - No public GitHub repository available -

    What is Dgraph?

    Dgraph's goal is to provide Google production level scale and throughput, with low enough latency to be serving real time user queries, over terabytes of structured data. Dgraph supports GraphQL-like query syntax, and responds in JSON and Protocol Buffers over GRPC and HTTP.

    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.

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    What companies use Dgraph?
    What companies use GraphQL?
    See which teams inside your own company are using Dgraph or GraphQL.
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    What tools integrate with Dgraph?
    What tools integrate with GraphQL?
      No integrations found

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      What are some alternatives to Dgraph and GraphQL?
      Neo4j
      Neo4j stores data in nodes connected by directed, typed relationships with properties on both, also known as a Property Graph. It is a high performance graph store with all the features expected of a mature and robust database, like a friendly query language and ACID transactions.
      Titan
      Titan is a scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster. Titan is a transactional database that can support thousands of concurrent users executing complex graph traversals in real time.
      ArangoDB
      A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.
      Cayley
      Cayley is an open-source graph inspired by the graph database behind Freebase and Google's Knowledge Graph. Its goal is to be a part of the developer's toolbox where Linked Data and graph-shaped data (semantic webs, social networks, etc) in general are concerned.
      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.
      See all alternatives