Sidekiq might be a bit more popular than Hadoop. We know about 21 links to it since March 2021 and only 15 links to Hadoop. 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.
Hi there! I want to show off a little feature I made using hanami, htmx and a little bit of redis + sidekiq. - Source: dev.to / 14 days ago
Sidekiq https://sidekiq.org/: This one started as an open source project, once it got enough traction, the developer made a premium version of it, and makes money by selling licenses to businesses. Source: 6 months ago
> I'm not sure feature withholding has traditionally worked out well in the developer space. I think it's worked out well for Sidekiq (https://sidekiq.org). I really like their model of layering valuable features between the OSS / Pro / Enterprise licenses. - Source: Hacker News / 8 months ago
The code above isn't idempotent. If you run it twice, it will create two copies, which is probably not what you intended. Why is this important? Because most backend job processors like Sidekiq don't make any guarantees that your jobs will run exactly once. - Source: dev.to / about 1 year ago
Relevant Patio11 comment from 2016: > We don't donate to OSS software which we use, because we're legally not allowed to. > I routinely send key projects, particularly smaller projects, a request to quote me a commercial license of their project, with the explanation that I would accept a quote of $1,000 and that the commercial license can be their existing OSS license plus an invoice. My books suggest we've spent... - Source: Hacker News / over 1 year 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: about 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
The Apache™ Hadoop™ project develops open-source software for reliable, scalable, distributed computing. - Source: dev.to / over 1 year ago
Resque - Resque is a Redis-backed Ruby library for creating background jobs, placing them on multiple queues, and processing them later.
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.
delayed_job - Database based asynchronous priority queue system -- Extracted from Shopify - collectiveidea/delayed_job
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.