ObjectBox Java (Kotlin, Android) VS dgraph

When I first attempted to publish to F-Droid, I experienced several pipeline issues. After reading through the pipeline logs in GitLab, I realized that my application's database (ObjectBox) was not entirely FOSS compliant and was causing build failures. The following day was spent migrating my app to Room.

I would focus on Kotlin instead of Java, there's really no point in sticking to Java at this point. And when it comes to databases, some local ones that are pretty easy to get into are Realm and ObjectBox, SQLite can definitely be a bit overwhelming at the beginning.

Not sure what exactly the issue is in your case, but linux-aarch64 is already a supported platform for ObjectBox (with some dependencies on libc versions etc). Maybe raise an issue for https://github.com/objectbox/objectbox-java with your specific error output and some details on your setup?

Just to add to this, there's also Realm and ObjectBox as alternatives.

Adding ObjectBox [0] to the list.

[0] https://objectbox.io/

Obectbox

While - strictly speaking - "database" refers to a systematic collection of data, "Database Management System'', or DBMS, refers to the piece of software that provides an efficient and versatile method of working with data(eg: ObjectBox). However, often the term "database" is also used loosely to refer to a DBMS, and you will find most DBMS only use the term database in their name and communication.

Maybe this? I've been looking at it recently.

https://github.com/objectbox/objectbox-java is an alternative to Room.

Here's the issue

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.