Software Alternatives, Accelerators & Startups

Bootstrap VS Apache Spark

Compare Bootstrap VS Apache Spark and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Bootstrap logo Bootstrap

Simple and flexible HTML, CSS, and JS for popular UI components and interactions

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.
  • Bootstrap Landing page
    Landing page //
    2023-04-22
  • Apache Spark Landing page
    Landing page //
    2021-12-31

Bootstrap features and specs

  • Responsive Design
    Bootstrap's grid system ensures that webpages are responsive and adapt to different screen sizes seamlessly.
  • Pre-designed Components
    Bootstrap comes with a variety of pre-designed components like buttons, forms, modals, and navigation bars that streamline the development process.
  • Cross-browser Compatibility
    Bootstrap ensures that your website will function correctly across different browsers, reducing the time spent on debugging issues related to browser inconsistencies.
  • Extensive Documentation
    The documentation is comprehensive and well-organized, making it easier for developers to understand and implement Bootstrap features quickly.
  • Community Support
    With a large and active community, finding help and resources related to Bootstrap development is relatively easy.
  • Customizable
    Bootstrap allows you to customize the default styles and components using Sass variables, making it adaptable to any project needs.
  • CDN Support
    Bootstrap can be included via Content Delivery Networks (CDN), which can help to speed up the initial load time of your web pages.

Possible disadvantages of Bootstrap

  • Uniform Look
    Websites built with Bootstrap often look similar because many developers use the default styles and components without customization.
  • Overhead
    Including the entire Bootstrap library can add unnecessary weight to your project if you only use a small fraction of its features.
  • Learning Curve
    For beginners, the extensive set of features and classes can be overwhelming and take some time to learn.
  • Dependency on jQuery
    Older versions of Bootstrap heavily rely on jQuery, which can be a disadvantage for projects that aim to minimize dependencies.
  • Specific Structure
    Bootstrap works best when you adhere to its predefined structure and classes, which can limit flexibility for more complex or unique designs.
  • Customization Challenges
    Deep customization can be difficult and time-consuming, especially if you need to override many default styles and behaviors.
  • Performance Issues
    Using a large number of Bootstrap components can lead to performance issues, particularly on lower-end devices.

Apache Spark features and specs

  • Speed
    Apache Spark processes data in-memory, significantly increasing the processing speed of data tasks compared to traditional disk-based engines.
  • Ease of Use
    Spark offers high-level APIs in Java, Scala, Python, and R, making it accessible to a broad range of developers and data scientists.
  • Advanced Analytics
    Spark supports advanced analytics, including machine learning, graph processing, and real-time streaming, which can be executed in the same application.
  • Scalability
    Spark can handle both small- and large-scale data processing tasks, scaling seamlessly from a single machine to thousands of servers.
  • Support for Various Data Sources
    Spark can integrate with a wide variety of data sources, including HDFS, Apache HBase, Apache Hive, Cassandra, and many others.
  • Active Community
    Spark has a vibrant and active community, providing a wealth of extensions, tools, and support options.

Possible disadvantages of Apache Spark

  • Memory Consumption
    Spark's in-memory processing can be resource-intensive, requiring substantial amounts of RAM, which can drive up costs for large-scale deployments.
  • Complexity in Configuration
    To optimize performance, Spark requires careful configuration and tuning, which can be complex and time-consuming.
  • Learning Curve
    Despite its ease of use, mastering the full range of Spark's features and best practices can take considerable time and effort.
  • Latency for Small Data
    For smaller datasets or low-latency requirements, Spark might not be the most efficient choice, as other technologies could offer better performance.
  • Integration Overhead
    Though Spark integrates with many systems, incorporating it into an existing data infrastructure can introduce additional overhead and complexity.
  • Community Support Variability
    While the community is active, the support and quality of third-party libraries and tools can be inconsistent, leading to potential challenges in implementation.

Bootstrap videos

Is Bootstrap Still Worth It? -- 1 Design, 2 Code Bases.

More videos:

  • Review - BOOTSTRAP Review | Best CSS Library ?
  • Review - Should you use Bootstrap?

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

Category Popularity

0-100% (relative to Bootstrap and Apache Spark)
Developer Tools
100 100%
0% 0
Databases
0 0%
100% 100
Design Tools
100 100%
0% 0
Big Data
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 Bootstrap and Apache Spark

Bootstrap Reviews

22 Best Bootstrap Alternatives & What Each Is Best For
Bootstrap alternatives are a suite of different tools and frameworks that web developers and designers employ for creating dynamic, responsive websites and applications. These tools, like Bootstrap itself, offer pre-written code for different elements of a website - from typography and buttons to navigation bars and image carousels - but each has its unique features and...
Source: thectoclub.com
15 Top Bootstrap Alternatives For Frontend Developers in 2024
UIKit is a modular front-end framework like Bootstrap and a Bootstrap competitor designed to develop fast and powerful web interfaces. You can utilize it with HTML or JavaScript based on your preference. It offers built-in support for right-to-left languages and includes an extensive library of components. This framework like Bootstrap provides a convenient solution for...
Source: coursesity.com
9 Best Bootstrap Alternatives | Best Frontend Frameworks [2024]
The only downside it has as compared to Bootstrap and Foundation is it is only a CSS framework, which means no JavaScript. So you will have to write your own JavaScript or Jquery to toggle your dropdowns or perform other basic interactionhttps://bulma.io/s of the sort. Overall it is a great alternative to Bootstrap, which is also being updated very frequently.
Source: hackr.io
Top 10 Best CSS Frameworks for Front-End Developers in 2022
Bootstrap is one of the most popular CSS frameworks globally and received instant popularity because of its responsive design. It was also the first framework that gave priority to mobile devices. With Bootstrap, there is no need for a separate design for mobile viewing. You just need to add the necessary classes, and the website will adapt to the screen size based on the...
Source: hackr.io
15 Best CSS Frameworks: Professional Bootstrap and Foundation Alternatives
This is why Bootstrap is by far the most popular framework on the market. All developers have heard of Bootstrap, and more than 80% of them say they are happy using it.

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...

Social recommendations and mentions

Based on our record, Bootstrap should be more popular than Apache Spark. It has been mentiond 362 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.

Bootstrap mentions (362)

  • How to Build a Blog with Laravel (& Send Slack Notifications)
    This will show the posts passed from the controller in a row of cards. Please notice that you are linking to Bootstrap’s CDN for easy styling. If there are no posts, a message on a card saying that there are no posts will be shown. - Source: dev.to / 28 days ago
  • Overengineered Anchor Links
    Yeah, good point. It's kinda common to have a big footer. Examples: https://getbootstrap.com/, https://stake.us/ (casino) That way on desktop you could get away with a 50vh margin under the content and then another 50vh for the footer. - Source: Hacker News / about 2 months ago
  • The 3 Best Python Frameworks To Build UIs for AI Apps
    FastHTML allows developers to build modern web applications entirely in Python without touching JavaScript or React. As its name implies, it is quicker to begin with FastHTML. However, it does not have pre-built UI components and styling. Getting the best out of this framework requires the knowledge of HTMX and UI styling using CSS libraries like Tailwind and Bootstrap. - Source: dev.to / about 2 months ago
  • Tailwind CSS vs. Bootstrap: Which Framework is Better for Your Project?
    Bootstrap is one of the oldest and most established CSS frameworks, originally developed by Twitter in 2011. It takes a component-based approach to web development, providing a comprehensive collection of ready-to-use UI elements and prebuilt components. - Source: dev.to / 2 months ago
  • How I Vibe-Coded an App to Explore GitHub Topics and Trending Repositories
    For the frontend, I had no prior experience, so I relied entirely on Claude's capabilities. 🙏 Claude generated the entire frontend in pure JavaScript, HTML, and CSS, and even added Bootstrap to it. This not only saved me a significant amount of time but also made my application responsive and visually appealing. - Source: dev.to / 2 months ago
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Apache Spark mentions (70)

  • Every Database Will Support Iceberg — Here's Why
    Apache Iceberg defines a table format that separates how data is stored from how data is queried. Any engine that implements the Iceberg integration — Spark, Flink, Trino, DuckDB, Snowflake, RisingWave — can read and/or write Iceberg data directly. - Source: dev.to / 26 days ago
  • How to Reduce Big Data Analytics Costs by 90% with Karpenter and Spark
    Apache Spark powers large-scale data analytics and machine learning, but as workloads grow exponentially, traditional static resource allocation leads to 30–50% resource waste due to idle Executors and suboptimal instance selection. - Source: dev.to / 28 days ago
  • Unveiling the Apache License 2.0: A Deep Dive into Open Source Freedom
    One of the key attributes of Apache License 2.0 is its flexible nature. Permitting use in both proprietary and open source environments, it has become the go-to choice for innovative projects ranging from the Apache HTTP Server to large-scale initiatives like Apache Spark and Hadoop. This flexibility is not solely legal; it is also philosophical. The license is designed to encourage transparency and maintain a... - Source: dev.to / 2 months ago
  • The Application of Java Programming In Data Analysis and Artificial Intelligence
    [1] S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach. Pearson, 2020. [2] F. Chollet, Deep Learning with Python. Manning Publications, 2018. [3] C. C. Aggarwal, Data Mining: The Textbook. Springer, 2015. [4] J. Dean and S. Ghemawat, "MapReduce: Simplified Data Processing on Large Clusters," Communications of the ACM, vol. 51, no. 1, pp. 107-113, 2008. [5] Apache Software Foundation, "Apache... - Source: dev.to / 2 months ago
  • Automating Enhanced Due Diligence in Regulated Applications
    If you're designing an event-based pipeline, you can use a data streaming tool like Kafka to process data as it's collected by the pipeline. For a setup that already has data stored, you can use tools like Apache Spark to batch process and clean it before moving ahead with the pipeline. - Source: dev.to / 3 months ago
View more

What are some alternatives?

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

Tailwind CSS - A utility-first CSS framework for rapidly building custom user interfaces.

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

Materialize CSS - A modern responsive front-end framework based on Material Design

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

Bulma - Bulma is an open source CSS framework based on Flexbox and built with Sass. It's 100% responsive, fully modular, and available for free.

Apache Storm - Apache Storm is a free and open source distributed realtime computation system.