Webpack VS Google Cloud Dataflow

Webpack Reviews

Google Cloud Dataflow Reviews

Webpack mentions (220)

• Practical and Beginner friendly guide for speeding up your web-apps

  There are various tools available that manage the size of bundled assets. We are going to use the example of a popular and widely used bundler named Webpack, and practically look at many of the optimization techniques it offers. - Source: dev.to / 15 days ago

• JS Toolbox 2024: Essential Picks for Modern Developers Series Overview

  In part 3 We jump into the world of bundlers, comparing webpack, esbuild, vite, and parcel 2. This section aims to guide developers through each bundler, focusing on their performance, compatibility, and ease of use. - Source: dev.to / 3 months ago

• Webpack: The Web Module Bundler

  Thats all about Webpack Basic, there are lots of feature of webpack, You can check here: https://webpack.js.org/. - Source: dev.to / 3 months ago

• How to improve page load speed and response times: A comprehensive guide

  Many web pages use CSS and JavaScript files to handle various features and styles. Each file, however, requires a separate HTTP request, which can slow down page loading. Concatenation comes into play here. It involves combining multiple CSS or JavaScript files into a single file. As a result, pages load faster, reducing the time spent requesting individual files. Gulp, Grunt, and Webpack are some of the tools... - Source: dev.to / 3 months ago

• Build a Vite 5 backend integration with Flask

  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

Google Cloud Dataflow mentions (14)

• How do you implement CDC in your organization

  Imo if you are using the cloud and not doing anything particularly fancy the native tooling is good enough. For AWS that is DMS (for RDBMS) and Kinesis/Lamba (for streams). Google has Data Fusion and Dataflow . Azure hasData Factory if you are unfortunate enough to have to use SQL Server or Azure. Imo the vendored tools and open source tools are more useful when you need to ingest data from SaaS platforms, and... Source: over 1 year ago

• Here’s a playlist of 7 hours of music I use to focus when I’m coding/developing. Post yours as well if you also have one!

  This sub is for Apache Beam and Google Cloud Dataflow as the sidebar suggests. Source: over 1 year ago

• How are view/listen counts rolled up on something like Spotify/YouTube?

  I am pretty sure they are using pub/sub with probably a Dataflow pipeline to process all that data. Source: over 1 year ago

• Best way to export several GCP datasets to AWS?

  You can run a Dataflow job that copies the data directly from BQ into S3, though you'll have to run a job per table. This can be somewhat expensive to do. Source: over 1 year ago

• Why we don’t use Spark

  It was clear we needed something that was built specifically for our big-data SaaS requirements. Dataflow was our first idea, as the service is fully managed, highly scalable, fairly reliable and has a unified model for streaming & batch workloads. Sadly, the cost of this service was quite large. Secondly, at that moment in time, the service only accepted Java implementations, of which we had little knowledge... - Source: dev.to / about 2 years ago