beam VS Express

The "streaming systems" book answers your question and more: https://www.oreilly.com/library/view/streaming-systems/97814.... It gives you a history of how batch processing started with MapReduce, and how attempts at scaling by moving towards streaming systems gave us all the subsequent frameworks (Spark, Beam, etc.).

As for the framework called MapReduce, it isn't used much, but its descendant https://beam.apache.org very much is. Nowadays people often use "map reduce" as a shorthand for whatever batch processing system they're building on top of.

Apache Beam is one of many tools that you can use

Flexible runtime ☁️: Temporian programs can run seamlessly in-process in Python, on large datasets using Apache Beam.

To perform the tests I'm using a Kafka cluster on Kubernetes from the Beam repo (here).

Apache Beam: Streaming framework which can be run on several runner such as Apache Flink and GCP Dataflow

Apache Beam: Batch/streaming data processing 🔗Link

What you are looking for is Dataflow. It can be a bit tricky to wrap your head around at first, but I highly suggest leaning into this technology for most of your data engineering needs. It's based on the open source Apache Beam framework that originated at Google. We use an internal version of this system at Google for virtually all of our pipeline tasks, from a few GB, to Exabyte scale systems -- it can do it all.

That being said, there is a learning curve in understanding how Apache Beam works. Take a look at the beam website for more information.

Express.js Documentation

In the JavaScript ecosystem, there are guides for enabling SAML-based enterprise single sign-on in AdonisJS, Express.js, Next.js, Remix, and React with an Express.js backend.

Starting off strong with Express.js, the cool kid on the block for building web apps. It's lightweight, flexible, and doesn't throw a tantrum when you ask it to scale. With Express, you can handle HTTP requests like a pro, play around with middleware, set up routes without breaking a sweat, and render views that make your app look stunning. Big names like Netflix and Uber are already on board, and if it's good enough for them, it's definitely worth a peek.

express - one of the most popular middleware tools, lightweight and easy to learn. docs

Now we can install both Express and Socket.io libraries:

app.listen(3000); ``` Now you can run your server by executing `node index.js`. Your web application will be accessible at http://localhost:3000/, where you'll see "Hello, world!" displayed in your browser. Congratulations! 🎉 You've successfully set up basic routing with Express.js! This guide covered only the tip of the iceberg when it comes to utilizing Express.js features. Explore its extensive documentation (https://expressjs.com/) to discover more possibilities. Remember, with Express.js, you have the power to build efficient and scalable web applications. Happy coding!

Converting a large Express.js application from JavaScript to TypeScript can be a challenging task. For many applications, this represents a significant portion of their technical debt, as the process may span many days, if not months, and new changes are typically not allowed during the conversion.

Nitro is a nice https webserver that you can deploy everywhere. Comparing it to express, it doesn't need weird middlewares for json, it has a simple way to support caching, a file system router, tasks and scheduled tasks that avoid quite a few shell scripts, db:migrations etc, plugins, KV storages, SQL connectors, websockets...

ExpressoTS fully supports Express middleware.

As you might have seen from this PR and in our forums Meteor v3(it is still in beta, but you can follow the progress here) will be released with a new engine, expressjs.