As Dgraph is nearing its v0.8 release, we wanted to spend some time comparing it against Neo4j, which is the most popular graph database. We have divided this post into five parts:

1. Loading data
2. Querying
3. Issues faced
4. Features
5. Principles behind Dgraph

Dgraph team is super excited to present v0.7.1 of Dgraph . This version is the biggest step we’ve taken towards our production aim of v1.0. We’ve implemented 90% of all the features we had planned in our product roadmap, including replication and high-availability using RAFT protocol, indexing, filtering, sorting, geospatial queries, and backups.

We at Dgraph love Hugo and use it for our blog. It’s blazingly fast, supports Markdown is written in Go and is very easy to work with. Initially, we were confused between Hugo vs. having a publication on Medium but later decided to go with Hugo because of the factors mentioned above. One of the things that we found lacking in the Hugo ecosystem was a good theme that we could use for our blog.

Ever faced the problem of having multiple ports in an application, one for each service? In this post, I’m going to brief about how to run multiple services via the same listener port.

When I started building the initial version of the Dgraph Go client, we were looking for a serialization format which was fast, easy to use and supported multiple language runtimes. We finally implemented our client using Protocol Buffers which gave twice the speed and consumed two-third memory compared to JSON according to our benchmarks.