Drasi: Microsoft's open source data processing platform for event-driven systems

Very interesting choice of using Cypher[0]

In 2014, we built a similar type event-driven system (but specifically for document distribution (a document can be distributed to a target set of entities; if a new entity is added, we need to resolve which distributions match)) and also ended up using Cypher via Neo4j (because of the complex taxonomical structure of how we mapped entities).

It is a super underrated query language and while most of the queries could also be translated to relational SQL, Cypher's linear construction using WITH clauses is far, far easier to reason about, IMO.

EDIT: feel like the devs went overboard with the mix of languages. Shoehorned in C# Blazor? Using JS and Jest for e2e testing?

[0] https://drasi.io/reference/query-language/

> while most of the queries could also be translated to relational SQL, Cypher's linear construction using WITH clauses is far, far easier to reason about, IMO.

https://prql-lang.org/

Didn't look too deeply, but one of the keys with Cypher (at least in the context of graph databases) is that it has a nice way of representing `JOIN` operations as graph traversals.

    MATCH (p:Person)-[r]-(c:Company) RETURN p.Name, c.Name

Where `r` can represent any relationship (AKA `JOIN`) between the two collections `Person` and `Company` such as `WORKS_AT`, `EMPLOYED_BY`, `CONTRACTOR_FOR`, etc.

So I'd say that linear queries are one of the things I like about Cypher, but the clean abstraction of complex `JOIN` operations is another huge one.