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highlight.js VS Apache Mahout

Compare highlight.js VS Apache Mahout and see what are their differences

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highlight.js logo highlight.js

Highlight.js is a syntax highlighter written in JavaScript. It works in the browser as well as on the server.

Apache Mahout logo Apache Mahout

Distributed Linear Algebra
  • highlight.js Landing page
    Landing page //
    2023-09-25
  • Apache Mahout Landing page
    Landing page //
    2023-04-18

highlight.js features and specs

  • Wide Language Support
    Highlight.js supports a comprehensive range of programming languages out of the box, making it versatile for various projects.
  • Automatic Language Detection
    It can automatically detect the programming language of a code block, reducing the setup time and effort for developers.
  • Customization
    Highlight.js offers numerous themes and customization options, allowing developers to easily tailor the syntax highlighting to match their application's aesthetic.
  • Lightweight and Fast
    The library is lightweight and performs efficiently, ensuring quick load times and a seamless user experience.
  • Open Source
    As an open-source project, Highlight.js benefits from community contributions and is free to use, modify, and distribute.

Possible disadvantages of highlight.js

  • Limited Dynamic Features
    Highlight.js is primarily used for static code block highlighting and lacks advanced features like real-time editing or complex code analysis.
  • Manual Updates
    New languages or updates may not be immediately available, requiring users to manually update the library or find alternatives for less common languages.
  • Performance Degradation on Large Files
    Highlight.js may experience performance issues when rendering very large code files, potentially slowing down page load times.
  • Dependency Management
    As with many JavaScript libraries, managing dependencies and ensuring compatibility with other libraries or frameworks can be challenging.

Apache Mahout features and specs

  • Scalability
    Apache Mahout is designed to handle large data sets, leveraging Hadoop to process data in parallel across distributed computing clusters, which allows for scaling as data size increases.
  • Library of Algorithms
    Mahout offers a substantial collection of pre-built machine learning algorithms for clustering, classification, and collaborative filtering, making it easier to implement standard ML tasks without developing them from scratch.
  • Integration with Hadoop
    Seamless integration with the Hadoop ecosystem enables Mahout to efficiently process and analyze large-scale data directly within a Hadoop cluster using MapReduce.
  • Open Source
    As an open-source project under the Apache Software Foundation, Mahout benefits from continuous improvements and community support, providing transparency and flexibility for users.
  • Focus on Math
    Mahout emphasizes mathematically sound algorithms, ensuring accuracy and robustness in machine learning models, backed by a foundation in linear algebra.

Possible disadvantages of Apache Mahout

  • Complexity
    Although powerful, Mahout can be complex and difficult to use for beginners, as it requires understanding of both Hadoop and the underlying machine learning algorithms.
  • Limited Deep Learning Capabilities
    Mahout is primarily focused on traditional machine learning techniques and lacks support for more modern deep learning frameworks, which may limit its applicability for certain advanced use cases.
  • Declining Popularity
    Although once well-regarded, Mahout has seen a decline in popularity with more users favoring newer tools such as Apache Spark's MLlib, which offer improved performance and a broader range of capabilities.
  • Setup Overhead
    Setting up and configuring a Hadoop environment to run Mahout can be a non-trivial task, requiring considerable effort and resources, particularly in smaller projects or organizations without existing Hadoop infrastructure.
  • API Inconsistency
    Over time, the API has undergone changes which can cause compatibility issues or require significant code refactoring when upgrading to newer versions of Mahout.

highlight.js videos

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Apache Mahout videos

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Apache Mahout Tutorial-1 | Apache Mahout Tutorial for Beginners-1 | Edureka

More videos:

  • Tutorial - Machine Learning with Mahout | Apache Mahout Tutorial | Edureka

Category Popularity

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User comments

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Social recommendations and mentions

Based on our record, highlight.js seems to be a lot more popular than Apache Mahout. While we know about 55 links to highlight.js, we've tracked only 3 mentions of Apache Mahout. 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.

highlight.js mentions (55)

  • A better pkg.go.dev
    Every time a request come in, we forward it to the pkg.go.dev server, then append the highlight.js script to the response before sending it back to the client. - Source: dev.to / 3 months ago
  • Day 19: Highlight'em up! 🔖
    It supports 192 languages, just like a browser highlighter:. - Source: dev.to / 5 months ago
  • YouTube Embeds Are Bananas Heavy and It's Fixable
    Now we only need to force bloggers to stop using GitHub Gist embeds. Hugo (and probably other static site generators) has built-in support for code snippets with syntax highlighting, and more dynamic sites can rely on highlight.js which removes dependence on third-party services. It's just insane, using heavy iframes for small code snippets. https://gohugo.io/content-management/syntax-highlighting/... - Source: Hacker News / 10 months ago
  • Glimmer DSL for Web Ruby Integration with JavaScript Libraries
    Glimmer DSL for Web is a Ruby-in-the-Browser Web Frontend Framework that enables Rubyists to finally have Ruby productivity and happiness in the Frontend via a simpler, more intuitive, more straightforward, and more productive library than all JavaScript libraries like React, Angular, Ember, Vue, Svelte, etc.... Glimmer DSL for Web's Rails sample app "Sample Selector" has been upgraded with Code Syntax... - Source: dev.to / 12 months ago
  • Code Syntax highlighting in Next Js
    Let's get started by installing the highlight js. - Source: dev.to / over 1 year ago
View more

Apache Mahout mentions (3)

  • Apache Mahout: A Deep Dive into Open Source Innovation and Funding Models
    Apache Mahout stands as a prime example of how open source projects can thrive through community collaboration, transparent governance, and diversified funding strategies. Its integration of traditional corporate sponsorship and avant-garde blockchain tokenization demonstrates that sustainability in open source development is not only feasible but can also be dynamic and innovative. Whether you are a developer... - Source: dev.to / 2 months ago
  • In One Minute : Hadoop
    Mahout, a library of machine learning algorithms compatible with M/R paradigm. - Source: dev.to / over 2 years ago
  • 20+ Free Tools & Resources for Machine Learning
    Mahout Apache Mahout (TM) is a distributed linear algebra framework and mathematically expressive Scala DSL designed to let mathematicians, statisticians, and data scientists quickly implement their own algorithms. - Source: dev.to / about 3 years ago

What are some alternatives?

When comparing highlight.js and Apache Mahout, you can also consider the following products

Apache Archiva - Apache Archiva is an extensible repository management software.

Apache Ambari - Ambari is aimed at making Hadoop management simpler by developing software for provisioning, managing, and monitoring Hadoop clusters.

Asklayer - Get real answers from your customers with Asklayers surveys, quizzes, polls and more. Works on any website with zero code and includes enterprise level features such auto-segmentation, user tagging, branching, NPS & CSAT calculation.

Apache HBase - Apache HBase – Apache HBase™ Home

Apache Tika - Apache Tika toolkit detects and extracts metadata and text from different file types.

Apache Pig - Pig is a high-level platform for creating MapReduce programs used with Hadoop.

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