InversifyJS VS vulcan-sql

Take a class for which we are tasked to write a unit test. This class may have a dozen methods and a dozen more attributes. In my environment we were already using inversify to dependency inject into this class, and using container snapshot and restore as setup and teardown operators, in our jest test file. But it began getting out of control even after refactoring into test cases and test runners.

Inversify (https://inversify.io/) for IoC.

Alguns frameworks trabalham desta forma por padrão, como é o caso do Angular, quando este não é o padrão do framework que utilizamos podemos usar alguma biblioteca, como a Inversify ou tsyringe da Microsoft.

Using decorators required setting an --experimentalDecorators experimental compiler flag. Several popular TypeScript libraries, such as type-graphql and inversify, rely on this implementation.

inversify

It blows 🤯 my mind to think that my #opensource project InversifyJS has reached over 100 MILLION DOWNLOADS on npm. InversifyJS is a lightweight (<50KB) but powerful Inversion Of Control (IoC) container for #JavaScript applications powered by #TypeScript. It is used to implement Dependency Injection (DI) in thousands of applications, including high-profile products like Microsoft Sway and over forty thousand open source repositories on #GitHub and over two thousand open source packages on #npm.

we use https://inversify.io/ in production, it works great.

I am one of the members of an open-source project VulcanSQL, a Data API Framework for data applications that helps data folks create and share data APIs faster.

I am excited to introduce an open-source project that our team has recently been developing, all written in Typescript. VulcanSQL (https://vulcansql.com/) is a data API framework that allows data engineers to create APIs using only templated SQL (jinja).

Hi, thanks for you comment.

I'm William, contributor of VulcanSQL.

We're an API framework, not a database like ClickHouse. We enable data engineers to build data APIs fast on top of their OLAP, which including ClickHouse. In fact, you can see from our issues (https://github.com/Canner/vulcan-sql/issues/138), ClickHouse users actually ask us to bring ClickHouse connector to VulcanSQL.

VulcanSQL (https://vulcansql.com/) offers a powerful solution for building embedded analytics and automation use cases, and it leverages the impressive capabilities of DuckDB as a caching layer. This combination brings about cost reduction and a significant boost in performance, making it an excellent choice for those seeking to optimize their data processing architecture.