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Google Cloud Dataflow VS Apache Struts

Compare Google Cloud Dataflow VS Apache Struts and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Google Cloud Dataflow logo Google Cloud Dataflow

Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

Apache Struts logo Apache Struts

Apache Struts is an open-source web application framework for developing Java EE web applications.
  • Google Cloud Dataflow Landing page
    Landing page //
    2023-10-03
  • Apache Struts Landing page
    Landing page //
    2022-04-27

Google Cloud Dataflow features and specs

  • Scalability
    Google Cloud Dataflow can automatically scale up or down depending on your data processing needs, handling massive datasets with ease.
  • Fully Managed
    Dataflow is a fully managed service, which means you don't have to worry about managing the underlying infrastructure.
  • Unified Programming Model
    It provides a single programming model for both batch and streaming data processing using Apache Beam, simplifying the development process.
  • Integration
    Seamlessly integrates with other Google Cloud services like BigQuery, Cloud Storage, and Bigtable.
  • Real-time Analytics
    Supports real-time data processing, enabling quicker insights and facilitating faster decision-making.
  • Cost Efficiency
    Pay-as-you-go pricing model ensures you only pay for resources you actually use, which can be cost-effective.
  • Global Availability
    Cloud Dataflow is available globally, which allows for regionalized data processing.
  • Fault Tolerance
    Built-in fault tolerance mechanisms help ensure uninterrupted data processing.

Possible disadvantages of Google Cloud Dataflow

  • Steep Learning Curve
    The complexity of using Apache Beam and understanding its model can be challenging for beginners.
  • Debugging Difficulties
    Debugging data processing pipelines can be complex and time-consuming, especially for large-scale data flows.
  • Cost Management
    While it can be cost-efficient, the costs can rise quickly if not monitored properly, particularly with real-time data processing.
  • Vendor Lock-in
    Using Google Cloud Dataflow can lead to vendor lock-in, making it challenging to migrate to another cloud provider.
  • Limited Support for Non-Google Services
    While it integrates well within Google Cloud, support for non-Google services may not be as robust.
  • Latency
    There can be some latency in data processing, especially when dealing with high volumes of data.
  • Complexity in Pipeline Design
    Designing pipelines to be efficient and cost-effective can be complex, requiring significant expertise.

Apache Struts features and specs

  • Robust Framework
    Apache Struts is a mature and well-established framework for Java web applications, providing stable and reliable tools for enterprise-level applications.
  • MVC Architecture
    Struts adheres to the Model-View-Controller (MVC) design pattern, which separates business logic, presentation, and navigation, making code maintenance and development easier.
  • Extensive Documentation
    Struts has comprehensive documentation and a wealth of online resources, including tutorials, community forums, and user guides, which can support developers throughout their projects.
  • Rich Tag Library
    It comes with a rich set of custom tags that enhance the JSP (JavaServer Pages) to create dynamic web content easily.
  • Plugin Support
    Apache Struts supports various plugins that can extend its functionality, allowing developers to integrate additional features without much effort.

Possible disadvantages of Apache Struts

  • Steep Learning Curve
    New developers might find Struts challenging to learn due to its complexity and the need for a good understanding of the MVC architecture and Java web application development.
  • Configuration Overhead
    The framework requires extensive XML configuration, which can be cumbersome and time-consuming compared to convention-over-configuration frameworks.
  • Performance
    Struts can be slower than some newer, lighter frameworks due to its broader feature set and the overhead associated with its extensive configuration.
  • Security Vulnerabilities
    Struts has had notable security vulnerabilities in the past. Although patches and updates are available, it necessitates proactive monitoring and maintenance.
  • Outdated Compared to Modern Frameworks
    With the advent of modern frameworks like Spring MVC and JavaServer Faces, some developers consider Struts to be less up-to-date with the latest web development standards and practices.

Analysis of Google Cloud Dataflow

Overall verdict

  • Google Cloud Dataflow is a strong choice for users who need a flexible and scalable data processing solution. It is particularly well-suited for real-time and large-scale data processing tasks. However, the best choice ultimately depends on your specific requirements, including cost considerations, existing infrastructure, and technical skills.

Why this product is good

  • Google Cloud Dataflow is a fully managed service for stream and batch data processing. It is based on the Apache Beam model, allowing for a unified data processing approach. It is highly scalable, offers robust integration with other Google Cloud services, and provides powerful data processing capabilities. Its serverless nature means that users do not have to worry about infrastructure management, and it dynamically allocates resources based on the data processing needs.

Recommended for

  • Organizations that require real-time data processing.
  • Projects involving complex data transformations.
  • Users who already utilize Google Cloud Platform and need seamless integration with other Google services.
  • Developers and data engineers familiar with Apache Beam or those willing to learn.

Analysis of Apache Struts

Overall verdict

  • Apache Struts is a robust framework, suitable for building Java-based web applications, but it's crucial to stay vigilant regarding security updates.

Why this product is good

  • Apache Struts is known for its MVC framework, which is useful for creating well-structured and maintainable Java applications. It provides a range of comprehensive features like a flexible tag library, integration with other Java frameworks, and a strong support community. However, it has faced some high-profile security vulnerabilities in the past, underscoring the importance of keeping the framework timely updated.

Recommended for

  • Organizations developing enterprise-level Java applications
  • Developers familiar with Java and looking for a robust MVC framework
  • Teams interested in integrating their web applications with other Java technologies

Google Cloud Dataflow videos

+ Add

Introduction to Google Cloud Dataflow - Course Introduction

More videos:

  • Review - Serverless data processing with Google Cloud Dataflow (Google Cloud Next '17)
  • Review - Apache Beam and Google Cloud Dataflow

Apache Struts videos

+ Add

Finding and Fixing Apache Struts CVE-2017-5638 with Black Duck Hub

More videos:

  • Review - Apache Struts 2 - remote command execution
  • Review - Dark ambient drone music | Vulnerable Apache Struts installation under attack (Java, Jakarta)

Category Popularity

0-100% (relative to Google Cloud Dataflow and Apache Struts)

Google Cloud Dataflow

Apache Struts

Big Data
100 100%
Big Data
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
Data Dashboard
100 100%
Data Dashboard
0% 0
Web Frameworks
0 0%
Web Frameworks
100% 100

User comments

Share your experience with using Google Cloud Dataflow and Apache Struts. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Google Cloud Dataflow and Apache Struts

Google Cloud Dataflow Reviews

Top 8 Apache Airflow Alternatives in 2024
Google Cloud Dataflow is highly focused on real-time streaming data and batch data processing from web resources, IoT devices, etc. Data gets cleansed and filtered as Dataflow implements Apache Beam to simplify large-scale data processing. Such prepared data is ready for analysis for Google BigQuery or other analytics tools for prediction, personalization, and other purposes.
Source: blog.skyvia.com

Apache Struts Reviews

17 Popular Java Frameworks for 2023: Pros, cons, and more
You can integrate Struts with other Java frameworks to perform tasks that arenโ€™t built into the platform. For instance, you can use the Spring plugin for dependency injection or the Hibernate plugin for object-relational mapping. Struts also allows you to use different client-side technologies such as Jakarta Server Pages to build the frontend of your application.
Source: raygun.com
10 Best Java Frameworks You Should Know
Followed by Struts Framework, the next leading framework currently being used in the IT industry is the Wicket.
Source: www.simplilearn.com

Social recommendations and mentions

Based on our record, Google Cloud Dataflow should be more popular than Apache Struts. It has been mentiond 14 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.

Google Cloud Dataflow mentions (14)

  • How do you implement CDC in your organization
    Imo if you are using the cloud and not doing anything particularly fancy the native tooling is good enough. For AWS that is DMS (for RDBMS) and Kinesis/Lamba (for streams). Google has Data Fusion and Dataflow . Azure hasData Factory if you are unfortunate enough to have to use SQL Server or Azure. Imo the vendored tools and open source tools are more useful when you need to ingest data from SaaS platforms, and... Source: over 3 years ago
  • Hereโ€™s a playlist of 7 hours of music I use to focus when Iโ€™m coding/developing. Post yours as well if you also have one!
    This sub is for Apache Beam and Google Cloud Dataflow as the sidebar suggests. Source: almost 4 years ago
  • How are view/listen counts rolled up on something like Spotify/YouTube?
    I am pretty sure they are using pub/sub with probably a Dataflow pipeline to process all that data. Source: almost 4 years ago
  • Best way to export several GCP datasets to AWS?
    You can run a Dataflow job that copies the data directly from BQ into S3, though you'll have to run a job per table. This can be somewhat expensive to do. Source: almost 4 years ago
  • Why we donโ€™t use Spark
    It was clear we needed something that was built specifically for our big-data SaaS requirements. Dataflow was our first idea, as the service is fully managed, highly scalable, fairly reliable and has a unified model for streaming & batch workloads. Sadly, the cost of this service was quite large. Secondly, at that moment in time, the service only accepted Java implementations, of which we had little knowledge... - Source: dev.to / about 4 years ago
View more

Apache Struts mentions (2)

What are some alternatives?

When comparing Google Cloud Dataflow and Apache Struts, you can also consider the following products

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Grails - An Open Source, full stack, web application framework for the JVM

Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

Spark Mail - Spark helps you take your inbox under control. Instantly see whatโ€™s important and quickly clean up the rest. Spark for Teams allows you to create, discuss, and share email with your colleagues

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