Amazon just announced their new graph database service, called Amazon Neptune. As per a TechCrunch article,
Amazon Neptune has been optimized to handle billions of relationships and run queries within milliseconds.
It all started with a Github issue.
At Dgraph, we really care about user feedback. Most of what we’ve built starting January 2017, has been based what our community (that’s you!
We’re seeing more and more users who want to load massive data sets into Dgraph. Many users want to load billions of edges, and some even want to load up to 50 billion edges!
When we started working on Badger, the aim was to keep things stupid simple. We needed to get rid of Cgo from Dgraph codebase, while also building something which can perform really well.
Dgraph has its own custom query language based on GraphQL, called GraphQL+-. You can learn about the basics of GraphQL+- in our latest screencast that introduces you to writing queries in it, which can be found right below.
If you have been following us, you may know that we released Badger a few months ago. Badger is a simple, efficient, and persistent key-value store, written in a hipster language.
Crashes can occur for many different reasons and can manifest themselves in many different forms. A program can experience a segfault or uncaught exception.
Starting v0.8, we have aimed to focus purely on the stability and performance of Dgraph. Our feature set is at this point good enough for most users – so we’ve decided to freeze it until we reach v1.