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Based on our record, Hadoop should be more popular than delayed_job. It has been mentiond 16 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.
It is hard to imagine any big and complex Rails project without background jobs processing. There are many gems for this task: **Delayed Job, Sidekiq, Resque, SuckerPunch** and more. And Active Job has arrived here to rule them all. - Source: dev.to / 7 days ago
Obviously, that is not what I’ve expected from Delayed::Job workers. So I took the shovel and started digging into git history. Since the last release the only significant modification has been made in the internationalization. We’ve moved to I18n-active_record backend to grant the privilege to modify translations not only to developers but also to highly-educated mere mortals. - Source: dev.to / 7 days ago
So how do we trigger such a long-running process from a Rails request? The first option that comes to mind is a background job run by some of the queuing back-ends such as Sidekiq, Resque or DelayedJob, possibly governed by ActiveJob. While this would surely work, the problem with all these solutions is that they usually have a limited number of workers available on the server and we didn’t want to potentially... - Source: dev.to / about 2 years ago
Several gems support job queues and background processing in the Rails world — Delayed Job and Sidekiq being the two most popular ones. - Source: dev.to / over 2 years ago
Back in the day, before Sidekiq and such, we used Delayed Job https://github.com/collectiveidea/delayed_job. Source: over 2 years ago
Data analysis software is also widely used in the telecommunications industry to manage network performance, detect fraud, and analyze customer data. Telecommunications companies can use data analysis software to analyze network data in real-time, allowing them to identify and address issues quickly. In addition, data analysis software can help telecommunications companies identify new revenue streams and improve... - Source: dev.to / 9 days ago
Did you check out tools like https://hadoop.apache.org/ ? Source: about 1 year 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: over 1 year ago
There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 1 year ago
A copy of Hadoop installed on each of these machines. You can download Hadoop from the Apache website, or you can use a distribution like Cloudera or Hortonworks. - Source: dev.to / over 1 year ago
Sidekiq - Sidekiq is a simple, efficient framework for background job processing in Ruby
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Hangfire - An easy way to perform background processing in .NET and .NET Core applications.
PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.
Resque - Resque is a Redis-backed Ruby library for creating background jobs, placing them on multiple queues, and processing them later.
Apache Cassandra - The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.