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Based on our record, Apache Beam should be more popular than Centrifugo. It has been mentiond 14 times since March 2021. 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.
Take a look at Centrifugo - https://centrifugal.dev/ - it provides a way to build efficient real-time messaging system using standard Django without ASGI involved. Source: 11 months ago
Hello, I am an author of Centrifugo project (https://centrifugal.dev/). It's a WebSocket server which scales using Redis. Instead of the approach you described when every message is delivered to every server Centrifugo uses PUB/SUB in a way that every server subscribed only to channels which current server connections have. It should scale pretty well, and resubscribe to channels is super-efficient. All the load... Source: over 1 year ago
Hello, I am author of Centrifugo (https://centrifugal.dev/) project - WebSocket server which scales with Redis. We have several blog posts which may help to answer your questions and give you some real world numbers about using Redis for WebSocket apps. Some links:. Source: over 1 year ago
Https://centrifugal.dev/ It's go native you can even write your own using it's underlying centrifuge library. We use it currently in Production just the docker container to be honest is what we deploy and just use a small config file or flags. Source: over 1 year ago
Hey folks! Centrifugo is an open-source scalable real-time messaging server written in Go language. It's language-agnostic and can be used to build chat apps, live comments, multiplayer games, real-time data visualizations, collaborative tools, etc. In combination with any backend. Including NodeJS-based backend which is relevant to this subreddit. And while Javascript/Node ecosystem has good WebSocket tools, I... Source: almost 2 years ago
The "streaming systems" book answers your question and more: https://www.oreilly.com/library/view/streaming-systems/9781491983867/. 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... - Source: Hacker News / 4 months ago
Apache Beam is one of many tools that you can use. Source: 6 months ago
Apache Beam: Streaming framework which can be run on several runner such as Apache Flink and GCP Dataflow. - Source: dev.to / over 1 year ago
Apache Beam: Batch/streaming data processing 🔗Link. - Source: dev.to / over 1 year ago
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. Source: almost 2 years ago
Crossplane - The open source multicloud control plane. Contribute to crossplane/crossplane development by creating an account on GitHub.
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
Pushbullet - Pushbullet - Your devices working better together
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
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Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.