dgraph

Dgraph is an open-source, horizontally scalable and distributed GraphQL database built on a graph backend. According to its README, it provides ACID transactions, consistent replication and linearizable reads, and is designed from the ground up for a rich set of queries. As a native GraphQL database, it controls how data is arranged on disk to optimize query performance and throughput, aiming to reduce disk seeks and network calls in a cluster. The project states its goal is to offer Google production-level scale and throughput with low enough latency for real-time user queries over terabytes of structured data. It supports GraphQL query syntax and responds in JSON and Protocol Buffers over gRPC and HTTP. Dgraph is written in Go. Status and platforms: the README lists version v25 as production-ready and notes use in production at multiple Fortune 500 companies. Official support covers Linux/amd64 and Linux/arm64; official Mac and Windows support was dropped in 2021, though the project can still be built and used on other platforms without official support. Docker is the recommended testing and deployment method, with an official image and a standalone quick-start command. Building from source requires Go 1.27+ and build tools, with `make setup` and `make install`. The README suggests Dgraph may fit applications with many interconnected tables, sparse data, a need for a flexible schema, and performance at scale. It combines NoSQL-like scalability with SQL-like transactions and the ability to select, filter and aggregate data points, plus distributed joins, traversals and graph operations. A comparison table in the README contrasts Dgraph with Neo4j and JanusGraph across architecture, replication, shard rebalancing, query language, protocols, transactions, full-text search, regular expressions, geo search and license. Dgraph is described as sharded and distributed, with consistent replication, automatic data movement for shard rebalancing, a GraphQL-inspired language, gRPC/HTTP with JSON/RDF, distributed ACID transactions, and native full-text search, regular expressions and geo search under Apache 2.0. Documentation, community discussions, releases and contribution guidelines are linked, and the team maintains officially supported client libraries alongside community-contributed unofficial ones.