Software Alternatives, Accelerators & Startups

Apache Cordova VS Apache Spark

Compare Apache Cordova 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.

Apache Cordova logo Apache Cordova

Platform for building native mobile applications using HTML, CSS and JavaScript

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.
  • Apache Cordova Landing page
    Landing page //
    2023-01-17
  • Apache Spark Landing page
    Landing page //
    2021-12-31

Apache Cordova features and specs

  • Cross-Platform Development
    Apache Cordova enables developers to build applications for multiple platforms (iOS, Android, Windows, etc.) using a single codebase, which saves time and resources.
  • Use of Web Technologies
    Cordova allows the use of standard web technologies like HTML, CSS, and JavaScript, making it accessible for web developers to create mobile applications without needing to learn platform-specific languages.
  • Extensive Plugin Ecosystem
    Cordova provides a wide range of plugins that enable access to native device functionalities (such as the camera, accelerometer, GPS, etc.), allowing for more versatile app development.
  • Cost Effective
    By reducing the need for multiple native developers and leveraging a single web development team, Cordova can significantly cut down the costs of application development.
  • Open Source
    As an open-source project, Apache Cordova benefits from community support and contributions, leading to continuous improvements and a wealth of shared knowledge and code.

Possible disadvantages of Apache Cordova

  • Performance Issues
    Applications built with Cordova may experience performance issues, especially with complex graphical or computational tasks, as they are essentially web applications wrapped in a native container.
  • Limited Native Functionality
    Although Cordova provides many plugins, accessing the latest native features often requires custom development, which can be complicated and time-consuming.
  • Dependency on Plugins
    Developers often rely heavily on third-party plugins to access native features. If these plugins are not well-maintained, they can introduce compatibility issues and bugs.
  • User Experience
    The user experience of Cordova-based apps may not be as smooth or responsive as fully native applications, potentially leading to lower user satisfaction.
  • Security Concerns
    Using multiple plugins and technologies can increase the surface area for security vulnerabilities. Also, web-based applications can be more susceptible to common web security issues.

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 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.

Apache Cordova videos

Apache Cordova - Hello World from Android and iOS

More videos:

  • Review - What’s Your View on Apache Cordova?

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 Apache Cordova and Apache Spark)
Development Tools
100 100%
0% 0
Databases
0 0%
100% 100
JavaScript Framework
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 Apache Cordova and Apache Spark

Apache Cordova Reviews

Top 10 Flutter Alternatives for Cross-Platform App Development
Developed by Apache Cordova, PhoneGap is used extensively for developing cross-platform mobile with the use of several web technologies. It lets developers write code by using HTML, CSS & JavaScript and package it as a native app. Being a simple framework, it includes the largest collection of plugins that extend its wide functionality.
Top 5 Flutter Alternatives for Cross-Platform Development
Apache Cordova is an open-source mobile development framework that lets you create cross-platform apps using standard web technologies like HTML5, CSS3, and JavaScript. Like NativeScript, Apache Cordova is more accessible to developers comfortable with web development, especially Angular or VueJS.
Source: www.miquido.com
Exploring 15 Powerful Flutter Alternatives
Oracle Mobile Application Framework (MAF) offers cross-platform development using standards like HTML5 and JavaScript containerized via Apache Cordova. Oracle MAF delivers excellent offline support capabilities matching the needs of field service teams and remote inspectors. With tools like Oracle Database and middleware, MAF apps cache relevant data subsets locally while...
Top 10 Android Studio Alternatives For App Development
Apache Cordova is used for building mobile applications with the help of HTML, CSS, and Javascript. It is an open-source mobile application development framework that was created by Nitobi.
10 Best Android Studio Alternatives For App Development
Apache Cordova is a tool to develop Android App Development. It enables software engineers to build apps for Android mobile phones. Using HTML5, CSS3, JavaScript instead of relying on platform-specific APIs. Like those in Android, iOS or Windows phones. When you are using Apache Cordova APIs, an app can be developed without any native code (like Java, objective-C, etc.) from...
Source: techdator.net

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 Apache Cordova. 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.

Apache Cordova mentions (44)

  • Show HN: I Made a Web App to Bring Children's Drawings to Life
    This is truly amazing. Is there a 'How it Works' a 'Potentials' section? I work with things that push to inspire creativity and learning to foster the passion behind creativity and authentic works where otherwise we'd see how 'AI copies our work' and now we can see how AI can bring works to life and make them more fun. Over-all would you like to see schools adopting your project? I didn't see a contact form but... - Source: Hacker News / 5 months ago
  • PWAs wont replace native iOS apps
    Anyone have experience with/opinions on Apache Cordova? [1] It seems like it would solve most of the PWA issues. Although I vaguely recall reading that Apple is not too fond of apps that are basically just wrapped web views. [1] https://cordova.apache.org/. - Source: Hacker News / over 1 year ago
  • What's the latest way of submitting pwas to the app stores?
    Has anyone tried pwa builder?[2] Thank you for any insights! [0]https://cordova.apache.org/. - Source: Hacker News / over 1 year ago
  • Why does everyone "suddenly" hate Single Page Apps?
    A little over a decade ago, I worked on the open-source project Apache Cordova/Adobe PhoneGap, first at IBM and later at Adobe. Apache Cordova enables you to build mobile applications using HTML, CSS and JavaScript while targeting multiple platforms with one code base. In today’s technology landscape, mobile is dominated by iOS and Android. In the early 2010’s we were awash in mobile platforms from BlackBerry,... - Source: dev.to / over 2 years ago
  • The right way to build multi platform apps in 2023 using web tech. ?
    There are layers that offer access to native APIs like capacitor, cordova and nativescript. Apparently sometimes multiple of them should be used, but I didn't understand what are the differences even after reading the announcement. These seem to be frontend agnostic technologies and Capacitor is apparently the more modern choice at the moment. Source: over 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 1 month 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 1 month 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 / 3 months ago
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What are some alternatives?

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

React Native - A framework for building native apps with React

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

PhoneGap - Easily create apps using the web technologies you know and love: HTML, CSS, and JavaScript.

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

Ionic - Ionic is a cross-platform mobile development stack for building performant apps on all platforms with open web technologies.

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