A horizontally scalable, distributed GraphQL database with ACID transactions and real-time query performance.
Dgraph is a horizontally scalable and distributed GraphQL database with a graph backend, designed for high-performance graph operations at scale. It provides ACID transactions, consistent replication, and linearizable reads, making it suitable for real-time applications over terabytes of structured data. The database is built from the ground up to optimize query performance and throughput by controlling data arrangement on disk.
Developers and organizations building applications with complex, interconnected data that require scalable graph operations, such as those with more than 10 SQL tables connected via foreign keys or sparse data that doesn't fit elegantly into SQL tables. It targets users needing production-level scale and low latency for real-time queries.
Developers choose Dgraph for its native GraphQL support combined with distributed ACID transactions and automatic horizontal scalability, offering NoSQL-like scalability with SQL-like transaction guarantees. Its unique selling point is providing Google production-level scale and throughput with low latency, along with native full-text search, geo search, and automatic shard rebalancing without manual intervention.
high-performance graph database for real-time use cases
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Dgraph uses GraphQL-inspired query syntax natively, allowing seamless integration with GraphQL-based applications and reducing the need for additional translation layers, as highlighted in the README under 'Native GraphQL Support'.
Features a sharded and distributed architecture with automatic shard rebalancing, enabling handling of terabytes of data across clusters without manual intervention, making it suitable for high-scale production environments.
Provides ACID transactions across distributed nodes, ensuring data consistency and reliability for real-time applications, which is a key strength compared to other graph databases that lack this in community editions.
Offers native full-text search, regular expressions, and geospatial queries without relying on external indexing systems, simplifying the stack for applications requiring complex search functionalities.
Officially supports only Linux/amd64 and Linux/arm64, having dropped Mac and Windows support in 2021, which can hinder development and testing on non-Linux environments without Docker workarounds.
While Docker is recommended, deploying and managing a distributed cluster requires more configuration and operational expertise compared to single-server databases, potentially increasing initial setup time and maintenance overhead.
Compared to established alternatives like Neo4j, Dgraph has a smaller community and fewer third-party tools or integrations, which might limit available resources and support for niche use cases.
dgraph is an open-source alternative to the following products: