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PhoneGap VS Apache Spark

Compare PhoneGap VS Apache Spark and see what are their differences

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PhoneGap logo PhoneGap

Easily create apps using the web technologies you know and love: 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.
  • PhoneGap Landing page
    Landing page //
    2022-01-14
  • Apache Spark Landing page
    Landing page //
    2021-12-31

PhoneGap features and specs

  • Cross-Platform Development
    PhoneGap allows developers to create applications for multiple platforms, such as iOS and Android, using a single codebase. This reduces development time and effort.
  • Leverages Web Technologies
    PhoneGap uses standard web technologies like HTML, CSS, and JavaScript, making it accessible for web developers to transition into mobile app development without learning new languages.
  • Access to Native APIs
    PhoneGap provides access to native device features such as the camera, accelerometer, and file system through a unified JavaScript API, enabling rich, native-like user experiences.
  • Large Plugin Library
    PhoneGap has a wide range of plugins available, giving developers the flexibility to add various functionalities to their apps without having to write complex native code.
  • Open Source
    Being an open-source framework, PhoneGap is free to use and has a large community of developers contributing to its improvement and providing support.

Possible disadvantages of PhoneGap

  • Performance Issues
    Since PhoneGap apps rely on WebView components to render the user interface, they may not perform as well as fully-native apps, especially for graphics-intensive applications.
  • Limited Advanced Native Features
    While PhoneGap provides access to basic native functionalities, it may not support all the advanced features and optimizations available in native development.
  • Dependency on Plugins
    PhoneGap's reliance on plugins for additional functionalities can lead to compatibility issues, especially if the plugins are not actively maintained or updated.
  • UI Consistency
    Achieving a consistent look and feel across different platforms can be challenging, as PhoneGap utilizes web technologies that may render differently on iOS and Android.
  • Learning Curve for Performance Optimization
    While web developers might find it easy to start with PhoneGap, optimizing the app for performance, particularly on mobile devices, can require a significant amount of additional learning and tweaking.

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 PhoneGap

Overall verdict

  • As of the latest developments, PhoneGap has been deprecated and is no longer being actively maintained. Adobe, the company behind PhoneGap, has encouraged developers to switch to Apache Cordova, which is the open-source foundation of PhoneGap. Therefore, it is not recommended for new projects.

Why this product is good

  • PhoneGap was once popular for allowing developers to create mobile apps using HTML, CSS, and JavaScript, making it easy for web developers to transition into mobile app development. It provided cross-platform compatibility and leveraged web technologies to build applications for Android, iOS, and other platforms without needing to learn platform-specific languages.

Recommended for

    Developers who are currently using PhoneGap should consider migrating to Apache Cordova or exploring other modern alternatives for cross-platform development such as React Native, Flutter, or Xamarin.

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.

PhoneGap videos

+ Add

What is PhoneGap and Cordova?

More videos:

  • Review - Is phonegap any good ?
  • Review - Introduction to PhoneGap - An Open Source Framework

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 PhoneGap and Apache Spark)

PhoneGap

Apache Spark

Development Tools
100 100%
Development Tools
0% 0
Databases
0 0%
Databases
100% 100
JavaScript Framework
100 100%
JavaScript Framework
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 PhoneGap and Apache Spark

PhoneGap 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.
Source: www.moontechnolabs.com
Exploring 15 Powerful Flutter Alternatives
Adobe PhoneGap is a distribution of the open-source Apache Cordova project for building cross-platform mobile apps. PhoneGap makes integrating Adobe services for analytics, marketing automation, and monetization easy. For apps focused on advertising revenue or lead generation, PhoneGap can accelerate leveraging Adobe’s audience segmentation, funnel tracking, and attribution...
Source: positiwise.medium.com
Best Mobile App Development Tools for Kids
A technology used for cross-platform mobile app development is referred to as PhoneGap. All the problems which we have seen above can be solved by PhoneGap easily. PhoneGap is an open-source mobile application framework. It allows developers to develop applications using standard web APIs. PhoneGap was developed by Nitobe Software, which is known as Adobe.
Source: codinghero.ai
10 Best Android Studio Alternatives For App Development
PhoneGap is another kind of tool among alternatives. Using this tool, you can develop cross-platform applications. The PhoneGap is an open-source development tool. And this is used for building iPhone, Android, Blackberry and other mobile apps with JavaScript. If you are using PhoneGap then you can reduce the development cost, time and effort.
Source: techdator.net
Top JavaScript Frameworks For Mobile App Development
As one of the popular mobile app development framework, Adobe and Apache have Adobe PhoneGap. Its open-source and flexible nature has been the crux of its rising popularity. It utilizes the built-in JavaScript API to establish a connection with the native features of mobile devices and the OS. It has a large and robust backend for easy development of native mobile applications.
Source: medium.com

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 seems to be a lot more popular than PhoneGap. While we know about 70 links to Apache Spark, we've tracked only 1 mention of PhoneGap. 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.

PhoneGap mentions (1)

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 â€” 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 PhoneGap and Apache Spark, you can also consider the following products

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

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

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

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

React Native - A framework for building native apps with React

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

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