At Grapl, graphs are core to our analytics approach. We believe that clean, connected data is a necessary capability for security teams. Early on, we made the choice to use Dgraph, and it’s one of the best technical decisions we’ve made. Dgraph’s commitment to performance, without sacrificing on critically important features like ACID transactions, all while providing excellent community support, has allowed us to focus more on our business logic and less on tuning knobs in our database.
Dgraph benefits from its team’s years of accumulation in the fields of web search, deep traversals, knowledge graph, etc., which effectively solves the problems of graph segmentation and large fan-out problem. It is an excellent open source and distributed graph database. Badger is also an excellent KV store. Our team maintains hundreds of billions of relationships using Dgraph. It effectively solves the reading and writing of related data and it has excellent performance.
Dgraph shards the data to horizontally scale to hundreds of servers. It is designed to minimize the number of disk seeks and network calls.
Dgraph is built like a search engine. Queries are broken into sub-queries, which run concurrently to achieve low-latency and high throughput.
With distributed ACID transactions, you can focus on your application logic, instead of worrying about data integrity.
Dgraph automatically runs synchronous replication, so losing a hard disk or a server doesn't affect your services.
Dgraph ensures that data is evenly balanced across servers by automatically moving shards, improving resource utilization for high performance.
Written entirely in Go, Dgraph is available under the Apache 2.0 license for easy adoption.
Quick iteration is important to keep your users happy. An adaptable flexible schema works with you as your application design evolves.
Dgraph provides a user interface, so you can browse and manage your data, making it easier to stay on top of things.
Dgraph internal key-value store, Badger is designed to reduce RAM usage and rely on SSD for performance. That's fast and cheap.
Dgraph can easily scale to multiple machines, or datacenters. Its sharded storage and query processing were specifically designed to minimize the number of network calls.Watch More