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Slick VS Apache Spark

Compare Slick VS Apache Spark and see what are their differences

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Slick logo Slick

A jquery plugin for creating slideshows and carousels into your webpage.

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.
  • Slick Landing page
    Landing page //
    2023-05-10
  • Apache Spark Landing page
    Landing page //
    2021-12-31

Slick features and specs

  • Responsive
    Slick is designed to be fully responsive, ensuring that sliders adapt well to different device sizes and screen resolutions.
  • Touch Support
    Slick offers native touch support, enabling swipe and scroll functionalities on mobile devices to enhance user experience.
  • Ease of Use
    It is easy to implement and configure with a straightforward API and good documentation, making it accessible for developers of all skill levels.
  • Customizability
    Slick provides numerous options and settings to customize the behavior and appearance of sliders to fit specific needs.
  • Extensibility
    The plugin supports various methods, events, and custom settings, making it highly extensible for more complex use cases.
  • Performance
    Slick is optimized for performance, ensuring fast loading times and smooth transitions, even with a large number of slides.
  • Accessibility
    The slider is built with accessibility in mind, supporting keyboard navigation and ARIA attributes.

Possible disadvantages of Slick

  • File Size
    Slick's file size can be relatively large compared to other lightweight slider plugins, which might affect the overall page load time.
  • Dependency
    Slick relies on jQuery, meaning that you need to include jQuery in your project, which can be a disadvantage for those aiming to reduce dependencies.
  • Learning Curve
    Although generally easy to use, some advanced features and customizations may require a deeper understanding of the API and additional time to learn.
  • Customization Limitations
    While customizable, some users may find limitations when trying to implement specific or highly unique designs that fall outside the provided options.
  • Browser Compatibility Issues
    In some rare cases, users have reported bugs or inconsistencies in older browsers, which may require additional testing and fixes.
  • Infrequent Updates
    The plugin is not updated as frequently as some other popular libraries, which could lead to potential compatibility issues with newer technologies over time.

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.

Analysis of Slick

Overall verdict

  • Slick is considered a good choice for those looking for a powerful yet simple way to implement sliders. Its popularity and ongoing support from the community indicate its reliability and effectiveness.

Why this product is good

  • Slick is a well-regarded carousel/slider plugin for jQuery that is praised for its flexibility, ease of use, and feature-rich design. It supports touch, accessibility, and works well with a variety of screen sizes and types of content, making it a popular choice for developers looking to integrate sliders into their websites.

Recommended for

    Slick is recommended for web developers and designers who need a customizable, responsive, and efficient slider solution. It's particularly well-suited for projects that require touch-friendly interfaces or need to incorporate various multimedia content fluidly.

Analysis of Apache Spark

Overall verdict

  • Yes, Apache Spark is generally considered good, especially for organizations and individuals that require efficient and fast data processing capabilities. It is well-supported, frequently updated, and widely adopted in the industry, making it a reliable choice for big data solutions.

Why this product is good

  • Apache Spark is highly valued because it provides a fast and general-purpose cluster-computing framework for big data processing. It offers extensive libraries for SQL, streaming, machine learning, and graph processing, making it versatile for various data processing needs. Its in-memory computing capability boosts the processing speed significantly compared to traditional disk-based processing. Additionally, Spark integrates well with Hadoop and other big data tools, providing a seamless ecosystem for large-scale data analysis.

Recommended for

  • Data scientists and engineers working with large datasets.
  • Organizations leveraging machine learning and analytics for decision-making.
  • Businesses needing real-time data processing capabilities.
  • Developers looking to integrate with Hadoop ecosystems.
  • Teams requiring robust support for multiple data sources and formats.

Slick videos

Creature Ever-slick Review (Santa Cruz/NHS)

More videos:

  • Review - SLICK SL57 strat Unboxing & Review Guitarfetish Xaviere guitar
  • Review - Slick Gimbal Review

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 Slick and Apache Spark)
Database Tools
100 100%
0% 0
Databases
0 0%
100% 100
MySQL 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 Slick and Apache Spark

Slick Reviews

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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, Apache Spark should be more popular than Slick. It has been mentiond 70 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.

Slick mentions (40)

  • Looking for material to help create Image Sliders, from scratch.
    In the past, I have copied code from Slick Sliders on to the container to generate the animation, but would love to learn how to hand code this myself. I work with WordPress in my company, so alot of PHP is involved as well. Source: almost 2 years ago
  • Building a complex carousel like Slick Slider center mode but without jQuery
    I've tried a few things, like installing vue slick carousel but I'm getting a type error that I can't seem to fix. I looked around and could only find basic carousels, without that perspective and layer-stacking kind of stuff with the center one being on top of the others. Slick slider's center mode (https://kenwheeler.github.io/slick/) is cool, not exactly what I want but the closest at least, but it requires... Source: almost 2 years ago
  • How can I add an image slider as my cover header for my home page?
    Depending how confident you are with JQuery, and what page builder you’re using, you may be able to set up a Slick Slider or similar around the Cover Block and use multiple Cover Blocks as the slides. Source: almost 2 years ago
  • how can I make something like this?
    Try this => https://kenwheeler.github.io/slick/. Source: about 2 years ago
  • What do you all use for your sliders? Do you build them from scratch or use some kind of plugin?
    Years and years ago I used to use Malsup's jQuery Cycle plugin and then Cycle2 but these now seem long abandoned. I've also used both flexslider and slickslider but I'm wondering if there are better, more modern alternatives I could now be using instead to quickly create sliders or carousels. Source: about 2 years 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 / about 2 months 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 / about 2 months 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 / 3 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 / 3 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 / 4 months ago
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What are some alternatives?

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

Liquibase - Database schema change management and release automation solution.

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

Flyway - Flyway is a database migration tool.

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

Sequel Pro - MySQL database management for Mac OS X

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