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Centrifugo VS Amazon EMR

Compare Centrifugo VS Amazon EMR and see what are their differences

Centrifugo logo Centrifugo

Centrifugo can instantly deliver messages to application online users connected over supported transports (WebSocket, HTTP-streaming, SSE/EventSource, GRPC, SockJS, WebTransport).

Amazon EMR logo Amazon EMR

Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
  • Centrifugo Landing page
    Landing page //
    2023-05-06
  • Amazon EMR Landing page
    Landing page //
    2023-04-02

Centrifugo videos

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Amazon EMR videos

Amazon EMR Masterclass

More videos:

  • Review - Deep Dive into What’s New in Amazon EMR - AWS Online Tech Talks
  • Tutorial - How to use Apache Hive and DynamoDB using Amazon EMR

Category Popularity

0-100% (relative to Centrifugo and Amazon EMR)
Testing
100 100%
0% 0
Data Dashboard
0 0%
100% 100
Hard Drive Tools
100 100%
0% 0
Big Data
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Amazon EMR should be more popular than Centrifugo. It has been mentiond 10 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.

Centrifugo mentions (5)

  • Real Time Chat Via Python
    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
  • Communicating between a lot of clients with websockets.
    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
  • Why is redis used with websockets?
    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
  • Websocket server design
    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
  • GitHub - centrifugal/centrifuge-js: JavaScript client SDK to communicate with Centrifugo real-time messaging server from browser, NodeJS and React Native. Supports WebSocket, HTTP-streaming, EventSource, WebTransport and SockJS transports
    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

Amazon EMR mentions (10)

  • 5 Best Practices For Data Integration To Boost ROI And Efficiency
    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: over 1 year ago
  • What compute service i should use? Advice for a duck-tape kind of guy
    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
  • Processing a large text file containing millions of records.
    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: about 2 years ago
  • How to use Spark and Pandas to prepare big data
    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
  • Beginner building a Hadoop cluster
    Check out https://aws.amazon.com/emr/. Source: about 2 years ago
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What are some alternatives?

When comparing Centrifugo and Amazon EMR, you can also consider the following products

Crossplane - The open source multicloud control plane. Contribute to crossplane/crossplane development by creating an account on GitHub.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Pushbullet - Pushbullet - Your devices working better together

Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

Notify - Need More Info? Contact us to schedule a demo or request a trial or pricing information and see how Notify's solutions can help your organization. Request Now. © 2016 Notify Technology Corporation.

Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost