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Jenkins VS Apache Spark

Compare Jenkins VS Apache Spark and see what are their differences

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Jenkins logo Jenkins

Jenkins is an open-source continuous integration server with 300+ plugins to support all kinds of software development

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.
  • Jenkins Landing page
    Landing page //
    2023-04-15
  • Apache Spark Landing page
    Landing page //
    2021-12-31

Jenkins features and specs

  • Open Source
    Jenkins is an open-source tool, which means users can modify, share, and use it without licensing fees.
  • Large Plugin Ecosystem
    Jenkins has a robust plugin ecosystem with over 1,500 plugins, allowing extensive customization and functionality to fit various DevOps needs.
  • Active Community
    The active and large community of Jenkins users and developers provides extensive support, documentation, and shared solutions.
  • Platform Independent
    Jenkins can run on various platforms including Windows, macOS, and various Unix-like systems, providing flexibility in deployment.
  • CI/CD Capabilities
    Jenkins is well-suited for implementing Continuous Integration and Continuous Deployment (CI/CD) pipelines, facilitating automated build, test, and deployment processes.
  • Scalability
    It supports distributed builds using Master-Slave architecture, enabling you to scale your build and deployment processes across multiple machines.
  • Extensible
    Thanks to its plugin architecture, Jenkins can be extended to integrate with a variety of tools and services, making it highly adaptable.

Possible disadvantages of Jenkins

  • Complex Setup
    Initial setup and configuration of Jenkins can be complicated, especially for new users or large-scale environments.
  • Resource Intensive
    Jenkins can be resource-intensive, requiring significant memory and CPU, particularly for large projects or high-frequency builds.
  • Maintenance Overhead
    Due to its extensive plugin usage, keeping Jenkins and its plugins updated can be time-consuming and sometimes problematic.
  • Steep Learning Curve
    Learning to use Jenkins effectively can have a steep learning curve, particularly due to the need to understand its various plugins and configuration options.
  • User Interface
    The user interface of Jenkins is sometimes considered outdated and not as intuitive or user-friendly as some of its modern counterparts.
  • Security Vulnerabilities
    As with many open-source tools, Jenkins can have security vulnerabilities that need to be regularly addressed to ensure a secure environment.
  • Poor Plugin Compatibility
    Not all plugins are maintained equally, leading to potential compatibility issues or bugs when using multiple plugins together.

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.

Jenkins videos

+ Add

Mick Jenkins - The Circus Album Review | DEHH

More videos:

  • Review - Mick Jenkins - The Water[s] ALBUM REVIEW
  • Review - Mick Jenkins - THE WATERS First REACTION/REVIEW

Apache Spark videos

+ Add

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 Jenkins and Apache Spark)

Jenkins

Apache Spark

DevOps Tools
100 100%
DevOps Tools
0% 0
Databases
0 0%
Databases
100% 100
Continuous Integration
100 100%
Continuous Integration
0% 0
Big Data
0 0%
Big Data
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 Jenkins and Apache Spark

Jenkins Reviews

The Best Alternatives to Jenkins for Developers
Jenkins X, a new kind of Jenkins made for cloud environments and modern development practices, tries to make setting up and handling CI/CD pipelines easier. It uses Kubernetes along with GitOps ideas in order to offer teams working on cloud-native apps an automated way that is less complex when it comes to managing their project’s lifecycle.
Source: morninglif.com
Top 5 Jenkins Alternatives in 2024: Automation of IT Infrastructure Written by Uzair Ghalib on the 02nd Jan 2024
If you have searched about Jenkins alternatives and you are reading this article, then there must be one of the three reasons you are here. You are already using Jenkins and are fed up with facing different issues and looking for a change. Or maybe you haven’t faced any issues yet but have heard the stories about Jenkins issues and looking to avoid them by choosing an...
Source: attuneops.io
What Are The Best Alternatives To Ansible? | Attune, Jenkins &, etc.
Jenkin is a popular tool for performing continuous integration of software projects in the market. Plus, it continues the delivery of projects regardless of the platform you’re working on. And it is also responsible for handling any build or continuous integration with various testing and development technologies. As a product, Jenkins is more developer-centric and...
Source: www.apzomedia.com
Best 8 Ansible Alternatives & equivalent in 2022
Jenkins is an open-source continuous integration tool. It is written using the Java programming language. It facilitates real-time testing and reporting on isolated changes in a larger code base. This software similar to Ansible helps developers to quickly find and solve defects in their code base & automate testing of their builds.
Source: www.guru99.com
Top 10 Most Popular Jenkins Alternatives for DevOps in 2024
Jenkins may be a de-facto tool for CI/CD, but it’s no longer a shiny newcomer borne directly out of modern DevOps best practices. Although Jenkins is still relevant, newer tools can offer improved ergonomics and expanded functionality. These can be better suited to contemporary software delivery methods.
Source: spacelift.io

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...
Source: searchbusinessanalytics.techtarget.com
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...
Source: www.spec-india.com
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...
Source: www.analyticsinsight.net

Social recommendations and mentions

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

Jenkins mentions (7)

  • CircleCI vs. Jenkins
    Jenkins is an open-source automation server used for software continuous integration and delivery. It automates various tasks, such as building, testing, and deploying applications.  It is easily extendable due to its vast ecosystem of plugins, making it easy to integrate into version control systems like Git, build tools like Maven/Gradle, and deployment platforms like AWS and Docker. - Source: dev.to / 2 months ago
  • Automated delivery React / Vue app for each Pull Request.
    It will give you a possibility to find and solve problems faster, release more stable and higher quality products. Here we will use CircleCI, but you can use whatever you need (Jenkins, Travis CI, GitLab CI). - Source: dev.to / about 1 year ago
  • Is Jenkins dead? v2
    CloudBees Jenkins Platform is a commercial offering from CloudBees, it is not the Jenkins project itself (which is open source). Jenkins is alive and well. See https://jenkins.io. Source: almost 2 years ago
  • ELI5 what is Jenkins?
    Ok. I'm talking about this: https://jenkins.io/. Source: over 2 years ago
  • I wanted a self hosted alternative to Atlassian status page so I build my own application !
    Currently supported : Datadog, Jenkins, DNS, HTTP. Source: over 2 years ago
View more

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 / 28 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 / 29 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 Jenkins and Apache Spark, you can also consider the following products

CircleCI - CircleCI gives web developers powerful Continuous Integration and Deployment with easy setup and maintenance.

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

Codeship - Codeship is a fast and secure hosted Continuous Delivery platform that scales with your needs.

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

Travis CI - Simple, flexible, trustworthy CI/CD tools. Join hundreds of thousands who define tests and deployments in minutes, then scale up simply with parallel or multi-environment builds using Travis CI’s precision syntax—all with the developer in mind.

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

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