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Based on our record, Google Cloud Dataflow 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: 12 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
Imo if you are using the cloud and not doing anything particularly fancy the native tooling is good enough. For AWS that is DMS (for RDBMS) and Kinesis/Lamba (for streams). Google has Data Fusion and Dataflow . Azure hasData Factory if you are unfortunate enough to have to use SQL Server or Azure. Imo the vendored tools and open source tools are more useful when you need to ingest data from SaaS platforms, and... Source: over 1 year ago
This sub is for Apache Beam and Google Cloud Dataflow as the sidebar suggests. Source: over 1 year ago
I am pretty sure they are using pub/sub with probably a Dataflow pipeline to process all that data. Source: over 1 year ago
You can run a Dataflow job that copies the data directly from BQ into S3, though you'll have to run a job per table. This can be somewhat expensive to do. Source: over 1 year ago
It was clear we needed something that was built specifically for our big-data SaaS requirements. Dataflow was our first idea, as the service is fully managed, highly scalable, fairly reliable and has a unified model for streaming & batch workloads. Sadly, the cost of this service was quite large. Secondly, at that moment in time, the service only accepted Java implementations, of which we had little knowledge... - Source: dev.to / about 2 years ago
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