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React Boilerplate VS Google BigQuery

Compare React Boilerplate VS Google BigQuery and see what are their differences

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React Boilerplate logo React Boilerplate

Offline-first, highly scalable foundation for your next app

Google BigQuery logo Google BigQuery

A fully managed data warehouse for large-scale data analytics.
  • React Boilerplate Landing page
    Landing page //
    2023-09-18
  • Google BigQuery Landing page
    Landing page //
    2023-10-03

React Boilerplate features and specs

  • Established Structure
    React Boilerplate provides a well-organized and consistent project structure, making it easier for developers to follow best practices and maintain a scalable codebase.
  • Advanced Configuration
    The boilerplate offers a comprehensive setup with support for modern JavaScript features, including Webpack, Babel, and ESLint, reducing the need for manual configuration.
  • Redux Integration
    React Boilerplate comes with built-in support for Redux, helping manage application state efficiently and seamlessly.
  • Performance Optimization
    The boilerplate includes performance-focused tools and configurations such as code splitting, which helps in optimizing the application's performance.
  • Community and Documentation
    Being a popular project, React Boilerplate has extensive documentation and an active community, providing plenty of resources and support.
  • Testing Setup
    It includes testing frameworks like Jest and Enzyme, which facilitate writing and running tests for your React components and applications.

Possible disadvantages of React Boilerplate

  • Complex Initial Setup
    The extensive initial setup and configuration process might be daunting for beginners or developers unfamiliar with advanced React and Webpack configurations.
  • Overhead for Small Projects
    For small or simple projects, the boilerplate might feel like overkill, introducing unnecessary complexity and overhead.
  • Steep Learning Curve
    Due to its comprehensive nature and numerous built-in features, there can be a steep learning curve for developers who are new to the ecosystem.
  • Maintenance
    Keeping up with updates and changes in all included libraries and tools can be time-consuming and may require regular maintenance to ensure compatibility and security.
  • Customization Difficulties
    Altering the default configurations and structures to fit unique needs can sometimes be challenging and may require in-depth knowledge of the underlying tools.

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.

Analysis of React Boilerplate

Overall verdict

  • React Boilerplate is a solid choice for developers looking to kickstart their React projects with a robust and comprehensive setup. It is particularly beneficial for projects that require scalability and performance optimizations from the start. However, it might be overkill for small or simple applications, where a lighter setup could be more efficient.

Why this product is good

  • React Boilerplate is considered good by many developers because it provides a well-structured framework for building scalable and maintainable React applications. It includes best practices and optimizations out of the box, such as Redux for state management, code splitting for performance, and built-in tools for testing, linting, and transpiling. This allows developers to focus more on building features rather than configuring and setting up the infrastructure.

Recommended for

    React Boilerplate is recommended for mid to large-scale React projects, teams that value architecture and maintainability, and developers who want to enforce coding standards and best practices from the beginning. It's also ideal for projects that anticipate a need for additional features, as its modular structure allows for easier expansion.

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

React Boilerplate videos

+ Add

React Boilerplate com Redux e TypeScript

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

Category Popularity

0-100% (relative to React Boilerplate and Google BigQuery)

React Boilerplate

Google BigQuery

Developer Tools
100 100%
Developer Tools
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
React
100 100%
React
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using React Boilerplate and Google BigQuery. 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 React Boilerplate and Google BigQuery

React Boilerplate Reviews

We have no reviews of React Boilerplate yet.
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Google BigQuery Reviews

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 BigQuery’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 “heavy” queries that operate using a large set of data. This means it’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
16 Top Big Data Analytics Tools You Should Know About
Google BigQuery is a fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. It is a Platform as a Service that supports querying using ANSI SQL. It also has built-in machine learning capabilities.
Source: www.analytixlabs.co.in

Social recommendations and mentions

Based on our record, Google BigQuery should be more popular than React Boilerplate. It has been mentiond 42 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.

React Boilerplate mentions (10)

  • Redux developers, please stop doing this!
    I worked on a React project in 2019, I believe it was built on top of the react-boilerplate template, and the developer experience with Redux was so bad that I became a Vue developer. - Source: dev.to / 10 months ago
  • Top 5 React Boilerplates to Know in 2023
    2 React Boilerplate is a reliable and well-designed boilerplate in the Javascript UI Libraries, with 28.2k ratings on GitHub. The super-rich component and font base, together with Redux, Mocha, Redux-Saga, Jest, React Router, PostCSS, and reselect are all included. They support SEO indexing. Concentrating on app development and performance is more than enough. - Source: dev.to / over 2 years ago
  • Redux Sagas firing multiple times if injected in different containers
    We are using https://github.com/react-boilerplate/react-boilerplate and have a classic store layout with multiple components. Source: about 3 years ago
  • react-boilerplate authentication login page flashes on page reload
    I'm working on an app with a login page and the rest of the pages of the app (should be logged in to view). I'm using react-boilerplate. From this example, I edited my asyncInjectors.js file to have redirectToLogin and redirectToDashboard methods:. Source: about 3 years ago
  • Identity Server 4 Social Login for SPA
    I'm working on application using a Web API(asp.net core) and a SPA (react-boilerplate). I'm starting work in user registration/login and one of the requirements is to allow for user to sign in with facebook, google, etc. Source: about 3 years ago
View more

Google BigQuery mentions (42)

  • Every Database Will Support Iceberg — Here's Why
    This isn’t hypothetical. It’s already happening. Snowflake supports reading and writing Iceberg. Databricks added Iceberg interoperability via Unity Catalog. Redshift and BigQuery are working toward it. - Source: dev.to / about 2 months ago
  • RisingWave Turns Four: Our Journey Beyond Democratizing Stream Processing
    Many of these companies first tried achieving real-time results with batch systems like Snowflake or BigQuery. But they quickly found that even five-minute batch intervals weren't fast enough for today's event-driven needs. They turn to RisingWave for its simplicity, low operational burden, and easy integration with their existing PostgreSQL-based infrastructure. - Source: dev.to / 2 months ago
  • How to Pitch Your Boss to Adopt Apache Iceberg?
    If your team is managing large volumes of historical data using platforms like Snowflake, Amazon Redshift, or Google BigQuery, you’ve probably noticed a shift happening in the data engineering world. A new generation of data infrastructure is forming — one that prioritizes openness, interoperability, and cost-efficiency. At the center of that shift is Apache Iceberg. - Source: dev.to / 2 months ago
  • Study Notes 2.2.7: Managing Schedules and Backfills with BigQuery in Kestra
    BigQuery Documentation: Google Cloud BigQuery. - Source: dev.to / 4 months ago
  • Docker vs. Kubernetes: Which Is Right for Your DevOps Pipeline?
    Pro Tip: Use Kubernetes operators to extend its functionality for specific cloud services like AWS RDS or GCP BigQuery. - Source: dev.to / 7 months ago
View more

What are some alternatives?

When comparing React Boilerplate and Google BigQuery, you can also consider the following products

mvpbase - An MVP boilerplate marketplace where you can find developers and designers to make the first version of your SaaS product.

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

React Native Desktop - Build OS X desktop apps using React Native

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

Static Site Boilerplate - A better workflow for building modern static websites.

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.

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