Dgraph simplifies creating publishing systems that manage taxonomies, user roles, workflows, and semantic interconnectivity. Here are some key use cases where Dgraph stands out: Dgraph offers an extensive cloud offering, enabling quick deployment with minimal configuration.ĭgraph: Empowering Companies for Diverse Use Casesĭgraph is a versatile knowledge graph database that excels in web-centric applications due to its efficient handling of JSON data.It runs on Linux Ubuntu, deployable under Kubernetes, Docker, or Amazon virtual machines, providing flexible configurations.Dgraph is under an open-source (Apache 2.0) license, with enterprise features available in a separate commercial offering.Marginal Inferencing: Inferencing is possible but more complex than RDF systems basic inferencing can be done via lambdas.No JSON-LD: Lacks direct support for JSON-LD, but schema can be adapted to use GraphQL templates.W3C RDF Stack: Some limitations with RDF-related features like Sparql, OWL, and SHACL, but can be mitigated in JavaScript.Innovative Graph Database: Redefines graph database norms and expectations.Data Analytics: Utilizes the hybrid nature to leverage RDF capabilities and labeled property graphs for data science analytics.Visualization: Employs Ratel as a GUI for record management and graph visualization to show entity relationships.Security: Allows defining access control levels based on permissions, ensuring proper data visibility and updates.Multitenancy: Supports multiple graphs accessible only through namespaces, enabling multitenancy.Lambdas: Utilizes specialized functions to override GraphQL queries or mutations, enhancing flexibility.Extensions: Allows writing extensions (in JavaScript) for data analytics, reporting, comparisons, transitive closures, and document searches.LLM/AI Aware: Developing an API for integrating with AI-based systems like ChatGPT.DQL: Provides a declarative query language for graph traversal and generative output, complementing GraphQL.Facets: Supports facets corresponding to rdf-star expressions for annotations and version management.RDF Oriented: While using JSON as the native language, Dgraph can read and create RDF nt data.Performant: Powered by Go and modern internal indexing, offering competitive performance in the broader database space.Cloud Native: Easily deployable in the cloud, allowing shared content across multiple graphs on multiple data systems. Ease of Use: Designed to make GraphQL usage easy and seamless.It also allows developers to shape query responses, reducing client-side processing. Dgraph's version of GraphQL ensures transactional support for both queries and updates. GraphQL, introduced by Facebook in 2015, enables easy manipulation of JSON data stores like graphs. It combines the strengths of Labeled Property Graphs and RDF-based Knowledge Graphs, using GraphQL+- as its query language.
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