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Google BigQuery VS Apache Struts

Compare Google BigQuery VS Apache Struts and see what are their differences

Grapple
Do-It-Yourself Data Analytics & Business Intelligence, Powered by AI featured
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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Google BigQuery logo Google BigQuery

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

Apache Struts logo Apache Struts

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

Google BigQuery features and specs

  • Scalability
    BigQuery can effortlessly scale to handle large volumes of data due to its serverless architecture, thereby reducing the operational overhead of managing infrastructure.
  • Speed
    It leverages Google's infrastructure to provide high-speed data processing, making it possible to run complex queries on massive datasets in a matter of seconds.
  • Integrations
    BigQuery easily integrates with various Google Cloud Platform services, as well as other popular data tools like Looker, Tableau, and Power BI.
  • Automatic Optimization
    Features like automatic data partitioning and clustering help to optimize query performance without requiring manual tuning.
  • Security
    BigQuery provides robust security features including IAM roles, customer-managed encryption keys, and detailed audit logging.
  • Cost Efficiency
    The pricing model is based on the amount of data processed, which can be cost-effective for many use cases when compared to traditional data warehouses.
  • Managed Service
    Being fully managed, BigQuery takes care of database administration tasks such as scaling, backups, and patch management, allowing users to focus on their data and queries.

Possible disadvantages of Google BigQuery

  • Cost Predictability
    While the pay-per-use model can be cost-efficient, it can also make cost forecasting difficult. Unexpected large queries could lead to higher-than-anticipated costs.
  • Complexity
    The learning curve can be steep for those who are not already familiar with SQL or Google Cloud Platform, potentially requiring training and education.
  • Limited Updates
    BigQuery is optimized for read-heavy operations, and it can be less efficient for scenarios that require frequent updates or deletions of data.
  • Query Pricing
    Costs are based on the amount of data processed by each query, which may not be suitable for use cases that require frequent analysis of large datasets.
  • Data Transfer Costs
    While internal data movement within Google Cloud can be cost-effective, transferring data to or from other services or on-premises systems can incur additional costs.
  • Dependency on Google Cloud
    Organizations heavily invested in multi-cloud or hybrid-cloud strategies may find the dependency on Google Cloud limiting.
  • Cold Data Performance
    Query performance might be slower for so-called 'cold data,' or data that has not been queried recently, affecting the responsiveness for some workloads.

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 BigQuery

Overall verdict

  • Google BigQuery is a powerful and flexible data warehouse solution that suits a wide range of data analytics needs. Its ability to handle large volumes of data quickly makes it a preferred choice for organizations looking to leverage their data effectively.

Why this product is good

  • Google BigQuery is a fully-managed data warehouse that simplifies the analysis of large datasets. It is known for its scalability, speed, and integration with other Google Cloud services. It supports standard SQL, has built-in machine learning capabilities, and allows for seamless data integration from various sources. The serverless architecture means that users don't need to worry about infrastructure management, and its pay-as-you-go model provides cost efficiency.

Recommended for

  • Businesses requiring fast processing of large datasets
  • Organizations that already utilize Google Cloud services
  • Companies looking for a cost-effective, scalable analytics solution
  • Teams interested in using SQL for data analysis
  • Data scientists integrating machine learning with their data workflows

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 BigQuery videos

+ Add

Cloud Dataprep Tutorial - Getting Started 101

More videos:

  • Review - Advanced Data Cleanup Techniques using Cloud Dataprep (Cloud Next '19)
  • Demo - Google Cloud Dataprep Premium product demo

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 BigQuery and Apache Struts)

Google BigQuery

Apache Struts

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

User comments

Share your experience with using Google BigQuery 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 BigQuery and Apache Struts

Google BigQuery Reviews

Database for Data Analytics
Processing typeDescriptionUse casesCommon databasesProcessing typesProcesses data in scheduled intervals (hours, days). High-latency but cost-efficient for large datasets.Financial reporting, trend analysis, historical analyticsSnowflake, Amazon Redshift, Google BigQueryContinuously ingests and processes data with minimal latency for real-time decision-making.Fraud...
Source: blog.devart.com
Data Warehouse Tools
Google BigQuery: Similar to Snowflake, BigQuery offers a pay-per-use model with separate charges for storage and queries. Storage costs start around $0.01 per GB per month, while on-demand queries are billed at $5 per TB processed.
Source: peliqan.io
Top 6 Cloud Data Warehouses in 2023
You can also use BigQueryโ€™s columnar and ANSI SQL databases to analyze petabytes of data at a fast speed. Its capabilities extend enough to accommodate spatial analysis using SQL and BigQuery GIS. Also, you can quickly create and run machine learning (ML) models on semi or large-scale structured data using simple SQL and BigQuery ML. Also, enjoy a real-time interactive...
Source: geekflare.com
Top 5 Cloud Data Warehouses in 2023
Google BigQuery is an incredible platform for enterprises that want to run complex analytical queries or โ€œheavyโ€ queries that operate using a large set of data. This means itโ€™s not ideal for running queries that are doing simple filtering or aggregation. So if your cloud data warehousing needs lightning-fast performance on a big set of data, Google BigQuery might be a great...
Source: www.shipyardapp.com
Top 5 BigQuery Alternatives: A Challenge of Complexity
BigQuery's emergence as an attractive analytics and data warehouse platform was a significant win, helping to drive a 45% increase in Google Cloud revenue in the last quarter. The company plans to maintain this momentum by focusing on a multi-cloud future where BigQuery advances the cause of democratized analytics.
Source: blog.panoply.io

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 BigQuery seems to be a lot more popular than Apache Struts. While we know about 47 links to Google BigQuery, we've tracked only 2 mentions of Apache Struts. 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 BigQuery mentions (47)

  • Ruby on Rails Performance: 7 Lessons from Scaling FirstPromoter
    We migrated the analytics layer to Google BigQuery. Same queries that timed out in PostgreSQL now run in under 2 seconds. But not everything belongs in BigQuery โ€” we initially moved too aggressively and actually reverted some queries back when the added complexity wasn't justified. Our rule of thumb: if a query scans hundreds of thousands of rows or involves complex time-series aggregations, BigQuery. Everything... - Source: dev.to / 4 months ago
  • How to Analyze 47 Million Hacker News Posts: A Data Scientist's Dream Dataset Just Got Better
    Google BigQuery - For large-scale data processing and SQL-based analysis. - Source: dev.to / 4 months ago
  • What if ML pipelines had a lock file?
    Data Pipelines usually read from tables that change over time. Most of these tables are stored in a data warehouse like Amazon Redshift or Google BigQuery. Rows are added or removed. Backfills happen. A column gets renamed or its meaning changes. Even when teams snapshot data, those snapshots are often implicit, not recorded as part of the pipeline run itself. - Source: dev.to / 5 months ago
  • Best SQL Courses with Certificates for 2026
    SQL endures because it's the non-negotiable interface for relational data. Enterprise data storage still relies heavily on relational databases despite new alternatives. What makes SQL valuable for learners is transferabilityโ€”while dialects differ across PostgreSQL, SQL Server, and BigQuery, the fundamentals stay consistent. - Source: dev.to / 8 months ago
  • Why Your Snowflake Bill is High and How to Fix It with a Hybrid Approach
    Within classic cloud data warehouses, Google BigQuery presents a different pricing model. Its on-demand, per-terabyte-scanned pricing can be cost-effective for sporadic forensic queries. But it carries the risk of a runaway query where a single mistake leads to a massive bill. - Source: dev.to / 8 months ago
View more

Apache Struts mentions (2)

What are some alternatives?

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

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.โ€ŽWhat is Apache Spark?

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

Looker - Looker makes it easy for analysts to create and curate custom data experiencesโ€”so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

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

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

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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