cockroach VS dgraph

You absolutely can write very high performance software in Go, that's kind of the point. You can efficiently interface with C libraries. You can create the sort of software everyone says should be done in Rust, like databases and web servers and system orchestration and games and every other goddamn thing that people will say isn't the right choice for Go.

PostgreSQL Parser separated from CockroachDB, a distributed DB.

Spencer Kimball (now CEO at CockroachDB) wrote an interesting article on this topic in 2021 where they created spencerkimball/stargazers based on a Python script. So I started thinking: could I create a data pipeline using Nifi and Kafka (two OSS tools often used with Druid) to get the API data into Druid - and then use SQL to do the analytics? The answer was yes! And I have documented the outcome below. Here’s my analytical pipeline for Github stars data using Nifi, Kafka and Druid.

One of the most popular distributed DB is built in Go: https://www.cockroachlabs.com/

Recently, I worked on such an integration with Splunk. The Splunk dashboard files that emulate the DB Console are now available in our repo for everyone's benefit.

Technically not postgres, but could be worth checking out cockroach db, it can use any postgres driver from programming languages and is build for distribution. I recently moved from postgres to cockroach (with golang postgres driver) and didnt need to change a single query

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.

dgraph - Scalable, Distributed, Low Latency, High Throughput Graph Database.

Now let’s talk about saving questions and answers. The Trie data structure is a great fit for quickly identifying if a question exists in the database and then finding its answer. To store tree nodes and links between them, I used the graph database Dgraph. For this project, I created a free cloud repository on dgraph.io. A TrieNode looks like this:

4. Dgraph

GraphQL, as defined, is not a programming language and not capable of arbitrary computation. This is important to note, as many of the platforms and services that provide GraphQL APIs could lead one to think that GraphQL is providing much of the functionality in these platforms, when really it is merely the facade and presentation via API of the capabilities of the underlying systems and platforms (re: Hasura, AppSync, Astra, Atlas, Dgraph, Contentful, GraphCMS, etc).

In my opinion, DGraph is the best competition to Firestore there is (and much much more). Imagine Firestore with Subscriptions, plus a Graph Database for complex searching, plus any kind of relational data you can think of, wrapped in a GraphQL interface, or a backend custom language called DQL.