Hey all-- sorry for the delay. Just had this thread sent over to me. I’ll try to answer as best I can, but unfortunately, as with many database things, it’ll depend heavily on your specific situation.
tl;dr - Yes, Dgraph can scale to that sort of workload. At 100k writes per second and 10BN+ records, you’ll need to be really thoughtful about infra, query optimization, admin, etc. The primary consideration is scaling up alpha nodes, and then load-balancing writes across the cluster.
I’ve asked a few of our engineers to run a few tests to give you some more specific sizing considerations. Should have more for you next week.
In my experience what’s going to work best for your use case will vary a lot based on what you’ll do with the data. E.g., I’ve had customers end up offloading time-series data to another store and taking a rolled up subset and putting it into Dgraph or using some sort of stream processing to only write the “interesting” bits.
10BN+ nodes with 100k writes per second on Dgraph alone is definitely possible, but you’ll need several alphas and will need to work to balance writes across the cluster. The number of alphas you need and the sizing for them will vary depending on the complexity of the updates (am I doing a complex search to find out where to insert the update?), as well as whether I am writing many of the same types of data or am hitting different predicates?
Can you share a bit more about what you’re building?