Software Alternatives, Accelerators & Startups

Apache Spark VS Parcel

Compare Apache Spark VS Parcel and see what are their differences

Apache Spark logo Apache Spark

Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

Parcel logo Parcel

Blazing fast, zero configuration web application bundler
  • Apache Spark Landing page
    Landing page //
    2021-12-31
  • Parcel Landing page
    Landing page //
    2021-12-13

Apache Spark videos

Weekly Apache Spark live Code Review -- look at StringIndexer multi-col (Scala) & Python testing

More videos:

  • Review - What's New in Apache Spark 3.0.0
  • Review - Apache Spark for Data Engineering and Analysis - Overview

Parcel videos

Danby Parcel Guard Smart Mailbox blogger Review

More videos:

  • Review - PARCEL MOVIE REVIEW | SASWATA CHATTERJEE | RITUPARNA SENGUPTA | RUPAM'S REVIEW
  • Review - Le Parcel Box review

Category Popularity

0-100% (relative to Apache Spark and Parcel)
Databases
100 100%
0% 0
Web Application Bundler
0 0%
100% 100
Big Data
100 100%
0% 0
JS Build Tools
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Spark and Parcel

Apache Spark Reviews

15 data science tools to consider using in 2021
Apache Spark is an open source data processing and analytics engine that can handle large amounts of data -- upward of several petabytes, according to proponents. Spark's ability to rapidly process data has fueled significant growth in the use of the platform since it was created in 2009, helping to make the Spark project one of the largest open source communities among big...
Top 15 Kafka Alternatives Popular In 2021
Apache Spark is a well-known, general-purpose, open-source analytics engine for large-scale, core data processing. It is known for its high-performance quality for data processing – batch and streaming with the help of its DAG scheduler, query optimizer, and engine. Data streams are processed in real-time and hence it is quite fast and efficient. Its machine learning...
5 Best-Performing Tools that Build Real-Time Data Pipeline
Apache Spark is an open-source and flexible in-memory framework which serves as an alternative to map-reduce for handling batch, real-time analytics and data processing workloads. It provides native bindings for the Java, Scala, Python, and R programming languages, and supports SQL, streaming data, machine learning and graph processing. From its beginning in the AMPLab at...

Parcel Reviews

Rollup v. Webpack v. Parcel
Parcel's caching feature sees dramatically decreases in time consumption after the initial run. For frequent, small changes, in smaller projects **Parcel*8 is a great choice.
Source: x-team.com
If you’ve ever configured Webpack, Parcel will blow your mind!
document.body.className = document.body.className.replace(/(^|\s)is-noJs(\s|$)/, "$1is-js$2")HomepageHomepageJavascriptBecome a memberSign inGet startedIf you’ve ever configured Webpack, Parcel will blow your mind!And how to hit the ground running with Parcel.Ibrahim ButtBlockedUnblockFollowFollowingMar 16, 2018Click here to share this article on LinkedIn »Zero...
Source: medium.com
First impressions with Parcel JS
The big selling point of Parcel though is that it offers a zero configuration experience. This means all the features are available out of the box! It also boasts blazing fast bundle times 👟 You won’t be configuring how Parcel works or having to draft in various plugins to get started. If you do need something, Parcel magically detects this and will pull in stuff for you on...
Source: codeburst.io
Parcel vs webpack - Jakob Lind
Parcel has made their own benchmarks of Parcel and other bundlers. Parcel has been criticized because they have not made the benchmarks open source. People cannot verify that the benchmarks are true when they are not open source.

Social recommendations and mentions

Based on our record, Parcel should be more popular than Apache Spark. 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.

Apache Spark mentions (56)

  • Groovy 🎷 Cheat Sheet - 01 Say "Hello" from Groovy
    Recently I had to revisit the "JVM languages universe" again. Yes, language(s), plural! Java isn't the only language that uses the JVM. I previously used Scala, which is a JVM language, to use Apache Spark for Data Engineering workloads, but this is for another post 😉. - Source: dev.to / 2 months ago
  • 🦿🛴Smarcity garbage reporting automation w/ ollama
    Consume data into third party software (then let Open Search or Apache Spark or Apache Pinot) for analysis/datascience, GIS systems (so you can put reports on a map) or any ticket management system. - Source: dev.to / 4 months ago
  • Go concurrency simplified. Part 4: Post office as a data pipeline
    Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 5 months ago
  • Five Apache projects you probably didn't know about
    Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 5 months ago
  • Spark – A micro framework for creating web applications in Kotlin and Java
    A JVM based framework named "Spark", when https://spark.apache.org exists? - Source: Hacker News / 11 months ago
View more

Parcel mentions (103)

  • Create a typescript package with Parcel
    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 / about 19 hours ago
  • How and why do we bundle zx?
    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 / 10 days ago
  • DEMO - Voice to PDF - Complete PDF documents with voice commands using the Claude 3 Opus API
    It runs using Parcel, very simple and easy to setup. The app has 3 files:. - Source: dev.to / 18 days ago
  • React Server Components Example with Next.js
    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 / 29 days 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
View more

What are some alternatives?

When comparing Apache Spark and Parcel, you can also consider the following products

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

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 Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

17track - All-in-one package tracking

Hadoop - Open-source software for reliable, scalable, distributed computing

rollup.js - Rollup is a module bundler for JavaScript which compiles small pieces of code into a larger piece such as application.