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Based on our record, Apache HTTP Server should be more popular than Hadoop. It has been mentiond 50 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.
Single-page applications (SPAs) existed before S3, but given that you still had to set up, scale, and maintain servers using something like Apache or NGINX in order to serve them, the advantages for “Ops” or “DevOps” were not so different to running a “real server” with a language like PHP, python, or Java. - Source: dev.to / 3 months ago
Both Docusaurus and Starlight generate static sites. This means that theoretically, they can be deployed on any platform that supports deploying static sites (like Apache or NGINX). But both of them provide a significantly better developer experience if we deploy on their recommended platforms. - Source: dev.to / 3 months ago
Simiplicity is nice, but there are reasons why Perl and PHP were the popular choices for web stacks in the early 2000's--they are faster and easier to develop with than C and likely safer than C too. Mod_perl (https://perl.apache.org/) and mod_php (https://cwiki.apache.org/confluence/plugins/servlet/mobile?contentId=115522403#content/view/115522403) helped to make Apache httpd (https://httpd.apache.org/) the... - Source: Hacker News / 4 months ago
The Apache HTTP Server project was initially launched in 1995 by a group of web developers and administrators who sought to improve upon the existing web server software available at the time. The project has since evolved into a collaborative effort, with contributors from around the world working together to maintain and enhance the server. Today, the Apache HTTP Server is managed by the Apache Software... Source: about 1 year ago
Apache websites of friends and acquaintances. Source: about 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
Microsoft IIS - Internet Information Services is a web server for Microsoft Windows
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Apache Tomcat - An open source software implementation of the Java Servlet and JavaServer Pages technologies
Apache Cassandra - The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.
XAMPP - XAMPP is a free and open-source cross-platform web server that is primarily used when locally developing web applications.
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.