groupcache VS dgraph

As shown in the title, DREAMEMO is a distributed cache with out-of-the-box, high-scalability, modular-design features.The groupcache implementation is referenced, and re-structured, specific module differentiation is as follows:

I remember one of the first real-world uses of Go being the groupcache package: https://github.com/golang/groupcache (to serve Chrome downloads, IIRC?)

> comes with a cache filling mechanism. Whereas memcached just says "Sorry, cache miss", often resulting in a thundering herd of database (or whatever) loads from an unbounded number of clients (which has resulted in several fun outages), groupcache coordinates cache fills such that only one load in one process of an entire replicated set of processes populates the cache, then multiplexes the loaded value to all callers.

I read that group cache (https://github.com/golang/groupcache) can be used to sync servers around a key.

I've not tried this myself, but I've seen it suggested to use groupcache (https://github.com/golang/groupcache) to sync your servers.

https://github.com/golang/groupcache is managing distributed caching that addresses thundering herd problem of memcache.

How it goes sometimes. Check out https://github.com/golang/groupcache and of course the AWS golang SDK.

There is also groupcache, written by the same author as memcached, but better.

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.