Based on our record, Socket.io seems to be a lot more popular than Amazon EMR. While we know about 719 links to Socket.io, we've tracked only 10 mentions of Amazon EMR. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
There are various libraries that let you create a ws server (similar to how express lets you create an HTTP server) Https://www.npmjs.com/package/websocket Https://github.com/websockets/ws Https://socket.io/. - Source: dev.to / about 9 hours ago
Previously we created a chat with pusher. But this time we are going to do it with Socket.io. Socket.io is a NodeJS library. With it we can create our own servers. This is cheaper than using pusher server and we have more control on the code. - Source: dev.to / 10 days ago
The first is the script tag in the head of our HTML document that loads the Socket.IO client library. This script tag includes the Socket.IO client library that will communicate with our socket.io server from the code above. - Source: dev.to / 27 days ago
Before diving into this tutorial, if you find microservices mysterious, check out my previous article for a detailed explanation. In this hands-on tutorial, we'll build a real-time chat server using Node.js, Socket.io, RabbitMQ, and Docker. Get ready for a practical journey into the world of microservices! Let's begin. - Source: dev.to / 3 months ago
Now we will be implementing socket logic using socket.io for building websockets. This library provides an abstraction layer on top of WebSockets, simplifying the process of creating real-time applications. For better maintainability, it is recommended to create a separate file for socket calls. To do this, navigate to the src folder, create a folder named services, and inside it, create a file named socket.ts... - Source: dev.to / 4 months ago
There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: about 1 year ago
I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: almost 2 years ago
This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: almost 2 years ago
Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 2 years ago
Check out https://aws.amazon.com/emr/. Source: about 2 years ago
Firebase - Firebase is a cloud service designed to power real-time, collaborative applications for mobile and web.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Pusher - Pusher is a hosted API for quickly, easily and securely adding scalable realtime functionality via WebSockets to web and mobile apps.
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
SignalR - SignalR is a server-side software system designed for writing scalable Internet applications, notably web servers.
Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost