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Amazon Neptune vs Dgraph: What are the differences?
- Data Model: Amazon Neptune uses a property graph model, while Dgraph utilizes a graph database model with RDF (Resource Description Framework) triples, providing different ways to visualize and interact with data.
- Query Language: Amazon Neptune supports Apache TinkerPop Gremlin and SPARQL for querying data, whereas Dgraph uses GraphQL±, a query language specifically designed for graph databases, offering a more user-friendly approach.
- Scalability: Amazon Neptune is a fully managed service in AWS, providing automated scaling capabilities, while Dgraph is open-source and requires manual scaling to handle increased workloads, offering different scalability options.
- Consistency Model: Amazon Neptune offers strong consistency, ensuring data integrity, while Dgraph provides eventual consistency by default, allowing for more flexibility in data replication and synchronization.
- Community Support: Dgraph has a growing community with active contributors, forums, and documentation, fostering open collaboration and development, whereas Amazon Neptune has a more established support system being a service within AWS, offering enterprise-grade support options.
- Advanced Features: Amazon Neptune includes features like multi-region replication, integrated security with AWS IAM, and automated backups, providing advanced functionalities for enterprise use cases, while Dgraph focuses on features like distributed transactions, sharding for horizontal scaling, and ACID compliance.
In Summary, the key differences between Amazon Neptune and Dgraph lie in their data models, query languages, scalability options, consistency models, community support, and advanced features, catering to different use cases and preferences in graph databases.
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Learn MorePros of Amazon Neptune
Pros of Dgraph
Pros of Amazon Neptune
- Managed Service in AWS3
- High Performance3
- Support for RDF2
- Support for SPARQL2
- Easy to Use2
- W3C Standards Compliantr1
- ACID Compliant1
- Scalable1
Pros of Dgraph
- Graphql as a query language is nice if you like apollo3
- Easy set up2
- Low learning curve2
- Open Source1
- High Performance1
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Cons of Amazon Neptune
Cons of Dgraph
Cons of Amazon Neptune
- No UI to see graph1
Cons of Dgraph
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- No public GitHub repository available -
What is Amazon Neptune?
Amazon Neptune is a fast, reliable, fully-managed graph database service that makes it easy to build and run applications that work with highly connected datasets. The core of Amazon Neptune is a purpose-built, high-performance graph database engine optimized for storing billions of relationships and querying the graph with milliseconds latency.
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.
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What companies use Amazon Neptune?
What companies use Dgraph?
What companies use Amazon Neptune?
See which teams inside your own company are using Amazon Neptune or Dgraph.
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What tools integrate with Amazon Neptune?
What tools integrate with Dgraph?
What tools integrate with Amazon Neptune?
What tools integrate with Dgraph?
No integrations found
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What are some alternatives to Amazon Neptune and Dgraph?
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.
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.
OrientDB
It is an open source NoSQL database management system written in Java. It is a Multi-model database, supporting graph, document, key/value, and object models, but the relationships are managed as in graph databases with direct connections between records.
JanusGraph
It 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. It is a transactional database that can support thousands of concurrent users executing complex graph traversals in real time.
TigerGraph DB
It is the only scalable graph database for the enterprise which is based on the industry’s first Native and Parallel Graph technology.
It unleashes the power of interconnected data, offering organizations deeper insights and better outcomes.
It’s proven technology supports applications such as IoT, AI and machine learning to make sense of ever-changing big data.