Parcel
Webpack
17track
rollup.js
AfterShip
esbuild
Vite
Grunt
Hadoop
Apache Spark
PostgreSQL
Apache Flink
Apache Cassandra
MongoDB
Apache Storm
Apache Kafka
Parcel HadoopBased on our record, Parcel should be more popular than Hadoop. It has been mentiond 103 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.
Parcel is a fast and zero-configuration web application bundler designed to simplify the build process for modern web projects. It's not limited to web applications, and it can be used to build packages targeting the browser or Node.js. - Source: dev.to / 15 days ago
At first we wanted to just get rid of all the helper utilities. Keep only the kernel, but this would mean a loss of backward compatibility. We needed some efficient code processing instead with recomposition and tree-shaking. We needed a bundler. But which one? Our testing approach relies on targets, not sources. We rebuilt the project frequently, speed was critical requirement. In essence, we chose a solution... - Source: dev.to / 24 days ago
It runs using Parcel, very simple and easy to setup. The app has 3 files:. - Source: dev.to / about 1 month ago
In the Changelog Podcast episode referenced above, Dan Abramov alluded to Parcel working on RSC support as well. I couldn’t find much to back up that claim aside from a GitHub issue discussing directives and a social media post by Devon Govett (creator of Parcel), so I can’t say for sure if Parcel is currently a viable option for developing with RSCs. - Source: dev.to / about 1 month ago
Once you build a simple Vite backend integration, try not to complicate Vite's configuration unless you absolutely must. Vite has become one of the most popular bundlers in the frontend space, but it wasn't the first and it certainly won't be the last. In my 7 years of building for the web, I've used Grunt, Gulp, Webpack, esbuild, and Parcel. Snowpack and Rome came-and-went before I ever had a chance to try them.... - Source: dev.to / 3 months 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
Webpack - Webpack is a module bundler. Its main purpose is to bundle JavaScript files for usage in a browser, yet it is also capable of transforming, bundling, or packaging just about any resource or asset.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
17track - All-in-one package tracking
PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.
rollup.js - Rollup is a module bundler for JavaScript which compiles small pieces of code into a larger piece such as application.
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
