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Apache Spark VS Apache Tomcat

Compare Apache Spark VS Apache Tomcat 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 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 Tomcat logo Apache Tomcat

An open source software implementation of the Java Servlet and JavaServer Pages technologies
  • Apache Spark Landing page
    Landing page //
    2021-12-31
  • Apache Tomcat Landing page
    Landing page //
    2023-01-24

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.

Apache Tomcat features and specs

  • Open Source
    Apache Tomcat is an open-source software, which means it is freely available for use and modifications. This can significantly reduce the cost of ownership and allows for customization.
  • Community Support
    Being a widely-used open-source server, Tomcat has a large and active community of developers and users who contribute to its documentation, plugins, and forums, providing extensive support.
  • Lightweight
    Tomcat is designed to be a lightweight servlet container, making it faster and less resource-intensive compared to full-blown Java EE application servers.
  • Integration with Popular Frameworks
    Tomcat integrates well with popular Java frameworks such as Spring and Hibernate, making it easier for developers to deploy and manage web applications.
  • Easy to Set Up and Configure
    Tomcat is relatively easy to set up and configure, making it suitable for both development and production environments.
  • Frequent Updates
    Regular updates and patches are released to improve performance, security, and compatibility, ensuring the server is up-to-date with the latest web technologies.

Possible disadvantages of Apache Tomcat

  • Limited Functionality
    While Tomcat is a powerful servlet container, it lacks some of the advanced features found in full-fledged Java EE application servers, which might be necessary for complex enterprise applications.
  • Resource Management
    Tomcat's default configuration might not be suitable for high traffic web applications, requiring significant tweaking and tuning to handle heavy loads effectively.
  • Documentation Quality
    The documentation, while extensive, can sometimes be hard to navigate and understand, especially for beginners. This can slow down the learning curve.
  • Limited Built-in Tools
    Compared to other full-stack application servers, Tomcat comes with limited built-in tooling for monitoring, load balancing, and clustering, often requiring third-party solutions.
  • Security Concerns
    As with any open-source project, security vulnerabilities may emerge. It requires constant monitoring and timely updates to ensure security.
  • Lack of EJB Support
    Tomcat does not support Enterprise JavaBeans (EJB), limiting its use in scenarios where EJB is a crucial component of the architecture.

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

Apache Tomcat videos

Introducing Apache Tomcat 8.5

More videos:

  • Review - Webinar: Introduction to Apache Tomcat 8
  • Review - Tcat - The Leading Enterprise Apache Tomcat Application Server

Category Popularity

0-100% (relative to Apache Spark and Apache Tomcat)
Databases
100 100%
0% 0
Web And Application Servers
Big Data
100 100%
0% 0
Application Server
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 Spark and Apache Tomcat

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...

Apache Tomcat Reviews

FOSS | Top 15 Web Servers 2021
Java programs are run using Apache Tomcat. To be more precise, it is a Java servlet – a Java software component that expands the functionality of a web server. Apache Tomcat, released under the Apache License version 2, is used by 0.1% of websites worldwide.
Source: www.zentao.pm
4 Open Source Application Servers (Comparison and Review)
Apache Tomcat is an open-source implementation of several Java technologies. It is the result of a collaboration of the finest developers worldwide. You can get involved with the development in a number of ways.
Source: shadow-soft.com
Top 5 open source web servers
Apache Tomcat is an open source Java servlet container that functions as a web server. A Java servlet is a Java program that extends the capabilities of a server. Although servlets can respond to any types of requests, they most commonly implement applications hosted on Web servers. Such web servlets are the Java counterpart to other dynamic web content technologies such as...
Source: opensource.com
Top 10 Open Source Java and JavaEE Application Servers
It is built upon a modular kernel powered by OSGi, and runs straight on top of the Apache Felix implementation. It is also capable of running with Equinox OSGi or Knopflerfish OSGi runtimes. HK2 abstracts the OSGi module system to provide components, which can also be viewed as services and injected into the run time and uses a derivative of Apache Tomcat as the servlet...

Social recommendations and mentions

Based on our record, Apache Spark should be more popular than Apache Tomcat. 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 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 / 17 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 / 18 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 / about 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 / about 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

Apache Tomcat mentions (17)

  • Java News: WildFly 36, Spring Milestones, and Open Liberty Updates
    Versions 11.0.6 and 9.0.104 of Apache Tomcat deliver new features and improvements. The release notes can be found for both versions. - Source: dev.to / 24 days ago
  • Artifactory: Centralizing Artifact Management for DevOps Success
    Download and Install Tomcat Before downloading, confirm the latest Tomcat build package from the official website. - Source: dev.to / 7 months ago
  • How to Deploy Applications Using Tomcat on a Web Server
    First, download the latest version of Tomcat from the official Apache Tomcat website. Choose the version that suits your needs, typically the latest stable release. - Source: dev.to / 11 months ago
  • Spring Boot Monitoring with Open-Source Tools
    Manual instrumentation allows you to define your Spans within the code itself rather than relying on automatic instrumentation finding the entry point for a trace. Manual instrumentation is especially helpful for applications that don’t use an application server such as Tomcat, JBoss, or Jetty. - Source: dev.to / over 1 year ago
  • Issue with chatgpy
    99% is a huge exaggeration. Two essential deployment tools off the top of my head: Https://tomcat.apache.org/ Https://docs.jboss.org/author/display/AS71/Developer%20Guide.html. Source: about 2 years ago
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What are some alternatives?

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

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

Microsoft IIS - Internet Information Services is a web server for Microsoft Windows

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

Apache HTTP Server - Apache httpd has been the most popular web server on the Internet since April 1996

Apache Hive - Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.

LiteSpeed Web Server - LiteSpeed Web Server (LSWS) is a high-performance Apache drop-in replacement.