graphql-bench VS dgraph

(from Hasura)

Scaling subscriptions is hard, but we work with our users/customers at scale to make sure settings are tweaked correctly.

We have users running 100k - 1M concurrent users in production for live-event type platforms. It's not completely trivial to benchmark and setup because query patterns, streaming vs live queries etc have an impact, but it works very reliably. No missing events, no problems disconnecting/reconnecting, no need for sticky sessions and so on.

An initial POC benchmark [1] should be a quick affair so if you're trying it out and run into any problems, please hit me up! Email on my bio.

[1]: https://github.com/hasura/graphql-bench

Has anyone come across neat tools for load-testing streaming APIs?

We used https://github.com/hasura/graphql-bench and a set of scripts to monitor runtime characteristics of Hasura and Postgres, and reconciliation to make sure data was received as expected and in-order.

But would love to see if there's other tools that folks have come across!

Just went through the examples -- I thought it was really neat!

Often times I want/need to display data in more than one format. Usually I just take up a bunch of page space by putting multiple charts.

Here's an example showing what I mean from actual project:

https://github.com/hasura/graphql-bench/raw/master/app/hasur...

If there was a solid and comprehensive charting library that could "tween" between the chart formats, only taking up the space of 1 chart, that would be a neat solution!

Have you found certain pairs/combinations of charts that expose hidden relationships when you display them by animating the data points between them?

Dgraph: A distributed and scalable graph database known for high performance. It's a good fit for large-scale graph processing, offering a GraphQL-like query language and gRPC API support.

Dgraph (GraphQL, DQL)

Have you tried dgraph.io?

DGraph – A distributed GraphQL database with a graph backend.

How does it compare to, say grakn (renamed https://vaticle.com/, I think?), or draph (https://dgraph.io/), or Ontotext's GraphDB (https://www.ontotext.com/products/graphdb/), or Datomic?

Consul Connect service mesh has a higher memory footprint, so on a small cluster with e5-medium nodes (2 vCPUs, 4 GB memory), you will only be able to support a maximum of 6 side-car proxies. In order to get an application like Dgraph working, which will have 6 nodes (3 Dgraph Alpha pods and 3 Dgraph Zero pods) for high availability along with at least one client, a larger footprint with more robust Kubernetes worker nodes were required.