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React Admin VS Google BigQuery

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

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

React Admin logo React Admin

A frontend Framework for building B2B applications running in the browser on top of REST/GraphQL APIs, using ES6, React and Material Design

Google BigQuery logo Google BigQuery

A fully managed data warehouse for large-scale data analytics.
  • React Admin Landing page
    Landing page //
    2023-08-20
  • Google BigQuery Landing page
    Landing page //
    2023-10-03

React Admin

Website
marmelab.com
Pricing URL
Official React Admin Pricing
$ Details
freemium โ‚ฌ135.0 / Monthly
Release Date
2017 January
Edit details

Google BigQuery

Website
cloud.google.com
Pricing URL
-
$ Details
Release Date
-
Edit details

React Admin features and specs

  • Component-Based Architecture
    React Admin utilizes a component-based architecture that promotes reusability and modularity, allowing developers to build complex interfaces with less effort.
  • Rich Ecosystem
    Being a React-based framework, React Admin benefits from a vast ecosystem of libraries and tools which can be easily integrated, providing enhanced functionality and scalability.
  • Customizable and Extensible
    Developers can customize and extend React Admin to fit specific needs, thanks to its high degree of flexibility and comprehensive support for custom components.
  • Built-in Data Providers
    React Admin comes with built-in data providers, making it easy to connect with a variety of REST, GraphQL, or other APIs out of the box.
  • Active Community and Maintenance
    Maintained by Marmelab, React Admin has an active community and is well-maintained, ensuring regular updates and improvements.

Possible disadvantages of React Admin

  • Steep Learning Curve
    Beginners might find React Admin challenging at first, especially if they are not familiar with React or the paradigm of component-based architecture.
  • Limited Server-Side Rendering
    React Admin is primarily designed for client-side rendering, which can be limiting for applications that require robust server-side rendering features for SEO purposes.
  • Opinionated Framework
    While being opinionated can be advantageous for some, it might restrict developers who are looking for more freedom in how they architect their applications.
  • Performance Overhead
    The abstraction and number of features included might introduce some performance overhead, especially in large-scale applications with complex data interactions.
  • Dependency on Third-Party Libraries
    React Admin's reliance on third-party libraries can sometimes lead to issues with compatibility or require additional learning for integration and use.

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 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 Admin videos

+ Add

10 Best React Admin Templates in 2022 | ReactJS Admin Templates

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 Admin and Google BigQuery)

React Admin

Google BigQuery

Developer Tools
100 100%
Developer Tools
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Design Tools
100 100%
Design Tools
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 React Admin and Google BigQuery

React Admin Reviews

We have no reviews of React Admin yet.
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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

Social recommendations and mentions

Based on our record, Google BigQuery should be more popular than React Admin. It has been mentiond 47 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 Admin mentions (26)

  • Top 20 Modern React Libraries To Supercharge Your Next Big Project
    Resource: React Admin Documentation. - Source: dev.to / over 1 year ago
  • How to build a CMS with Supabase and React-admin
    I've been working with react-admin on various projects, some of which required basic CMS features in addition to the core application. We've used headless CMS like Strapi, Directus, or Prismic for these features. However, react-admin is so powerful that it can be used to build the CMS part, too. That's why I worked on a CMS proof-of-concept using react-admin for the admin UI and Supabase (which provides a REST... - Source: dev.to / over 1 year ago
  • A Year of Transformation: Reflecting on 2024's Journey in Tech and Beyond
    I was learning React JS front end and in this journey of self learning, I have achieved many milestone like utilizing react-admin framework. I also implemented two-factor authentication using Authenticator tools with react-admin framework. It was a very challenging job to include two-factor alongside react-admin authentication as there is no tutorial available for it. But this is very much required in the era of... - Source: dev.to / over 1 year ago
  • Building a Complete React CRM App with Atomic CRM ๐Ÿ› ๏ธ
    With a simple relational data model, developers can easily modify the system to store additional data. Its component-based architecture allows for replacing or customizing any part of the application, giving developers full control over the user experience. Built using React and react-admin, two widely supported frameworks, it comes with a rich library of pre-built components ready for use. - Source: dev.to / almost 2 years ago
  • Major updates from the open source community: Release Radar ยท June 2024
    Whenever I see the word "framework", I can't help but think of the Linebreakers' song "We're Gonna Build a Framework". That aside, React-admin has over 25,000 users around the world. It's a single-page application framework, allowing you to build web apps running on top of REST/GraphQL APIs, using TypeScript, React and Material Design. React-admin's latest update brings refined lists and forms, dependency update,... - Source: dev.to / about 2 years ago
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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 / 5 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 / 6 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 / 9 months ago
View more

What are some alternatives?

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

Refine - A React Framework for building internal tools, admin panels, dashboards & B2B apps with unmatched flexibilty.

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

Mantine - React library, 60+ hooks and components with dark theme support and focus on accessibility

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.

Chakra UI - Simple, modular and accessible UI components for your React applications.

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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