“This was a key consideration for us and one of the main reasons we looked at graphs. Writing queries against graphs is far more natural than writing SQL queries. You don’t need to have a deep understanding of data schema or write across hundreds of joins.”
“Dgraph also gives us confidence in our ability to scale and take on new customers and opportunities — to tell a partner that we can scale quickly, limitlessly, and globally. It’s a completely new level. Forget about SQL and discover Dgraph.”
“Within 20 minutes, I had the entire structure of the data set with all the proper interactions captured in Dgraph. I didn't expect it to be as good as it was. We solved this entire problem in one hit. It was months in the planning and minutes in the execution in the final version."
“When we performed a stress test on a thousand concurrent queries, Dgraph was still able to maintain a response time of 50 ms, while simultaneously achieving 15000/s QPS; the performance is excellent.”
“The community that Dgraph has assembled is exceptional because it covers everything from new users just starting out to advanced users who have decades of experience. The community is much more than just getting technical support for existing functionality. Dgraph's community incorporates feature requests, best practices, newsworthy announcements, interesting blog posts, and referenced documentation.”
Stars on GitHub
Dive into this comprehensive research paper that explores topics including: Dgraph architecture, indexing, transaction and lock-free high availability transaction processing, consistency model, replication, high availability and scalability, queries, traversals, functions, filters, intersections.Download
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