memberlist VS dgraph

hashicorp/memberlist: go get -u github.com/hashicorp/memberlist

I use lightweight https://github.com/hashicorp/memberlist to build initial cluster skeleton (find out what are nodes constituting it)

Does https://github.com/hashicorp/memberlist count? It’s a gossip-based eventual consistency protocol based on SWIM.

An equivalent of golang's memberlist would be awesome.

I don't know the engineer that did it but I know what happened. There's a library that a bunch of foundational Amazon services use called DFDD. It uses a gossip protocol to handle service discovery and health checking. The open source equivalent is Hashicorp memberlist. To remove a node from the cluster, you have to send a command to an arbitrary node that says a node is dead.

serf uses memberlist which uses the SWIM failure detection protocol (https://www.cs.cornell.edu/projects/Quicksilver/public_pdfs/SWIM.pdf) with the Lifeguard extensions (https://arxiv.org/pdf/1707.00788.pdf).

https://github.com/hashicorp/memberlist

Fairly idiomatic/clean

This algorithm assumes you're doing that separately using some sort of membership protocol (e.g. SWIM), and you pass in the membership list that you are keeping up to date with that protocol. If you're curious about those, HashiCorp memberlist and HashiCorp Serf are really good to look at. I believe Consul uses those libraries under the hood.

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.