Dgraph vs Grakn: What are the differences?
Developers describe Dgraph as "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. On the other hand, Grakn is detailed as "An intelligent database - a knowledge graph". It is an intelligent database: a knowledge graph engine to organise complex networks of data and making it queryable, by performing knowledge engineering. Rooted in Knowledge Representation and Automated Reasoning, it provides the knowledge foundation for cognitive and intelligent (e.g. AI) systems, by providing an intelligent language for modelling, transactions and analytics. Being a distributed database, it is designed to scale over a network of computers through partitioning and replication.
Dgraph and Grakn can be primarily classified as "Graph Databases" tools.
Dgraph and Grakn are both open source tools. It seems that Dgraph with 12.8K GitHub stars and 910 forks on GitHub has more adoption than Grakn with 2K GitHub stars and 234 GitHub forks.