awesome-go-storage VS dgraph

Awesome Go Storage (GitHub)

Any many many more. Check https://github.com/gostor/awesome-go-storage

C is significantly slower at concurrency when implemented naively. It's as fast as languages like Go when implemented using the same techniques, which is not obvious and trivial to use like in a higher level GC'd language. GC actually helps out a ton there, for example look at the complexity of async/await in Rust which requires the notion of pinning.

https://github.com/gostor/awesome-go-storage#database

https://java-source.net/open-source/database-engines

Not a database but honorable mention, LMAX disrupter: https://lmax-exchange.github.io/disruptor/

You may want to start from here: awesome-go-storage and choose what fit your needs

This is neat! I am quite a fan of all the go based file systems that are springing up. Question: what are the main compare and contrast points between juice and seaweed fs?

Here is a compendium for those interested:

https://github.com/gostor/awesome-go-storage

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.