Software Alternatives, Accelerators & Startups

React Native Paper by Callstack VS Google BigQuery

Compare React Native Paper by Callstack VS Google BigQuery 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.

React Native Paper by Callstack logo React Native Paper by Callstack

Material Design for React Native (Android & iOS)

Google BigQuery logo Google BigQuery

A fully managed data warehouse for large-scale data analytics.
  • React Native Paper by Callstack Landing page
    Landing page //
    2023-10-16
  • Google BigQuery Landing page
    Landing page //
    2023-10-03

React Native Paper by Callstack features and specs

  • Cross-Platform Compatibility
    React Native Paper provides a consistent design and behavior across both iOS and Android platforms, allowing developers to build applications that work seamlessly on multiple devices.
  • Material Design Integration
    The library is based on Google's Material Design, offering a set of pre-built, highly customizable components that enable developers to achieve a cohesive look and feel for their applications.
  • Theming Support
    React Native Paper includes comprehensive theming support, allowing developers to easily switch themes and adjust colors to meet brand requirements or user preferences.
  • Active Community and Support
    Being maintained by Callstack, a company with significant expertise in React Native, ensures that React Native Paper is well-documented, frequently updated, and supported by an active community.
  • Customizable Components
    The components provided by React Native Paper are highly customizable, enabling developers to override default styles and functionalities to better suit their application's needs.

Possible disadvantages of React Native Paper by Callstack

  • Performance Overhead
    While React Native Paper provides many useful components, integrating it into a project can introduce some performance overhead, which might be noticeable in resource-constrained environments.
  • Learning Curve
    Developers new to React Native Paper or Material Design may face a learning curve understanding how to effectively use and customize the components according to the design guidelines.
  • Lacks Advanced Components
    Although React Native Paper covers most of the basic UI components, it may lack some advanced components or features, which might require developers to integrate additional libraries.
  • Dependency on Material Design
    Since React Native Paper relies heavily on Material Design principles, it may not be suitable for applications that require a unique or non-material design aesthetic.

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 Native Paper by Callstack videos

No React Native Paper by Callstack videos yet. You could help us improve this page by suggesting one.

Add video

Google BigQuery videos

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 Native Paper by Callstack and Google BigQuery)
React Native
100 100%
0% 0
Data Dashboard
0 0%
100% 100
Development Tools
100 100%
0% 0
Big Data
0 0%
100% 100

User comments

Share your experience with using React Native Paper by Callstack and Google BigQuery. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare React Native Paper by Callstack and Google BigQuery

React Native Paper by Callstack Reviews

We have no reviews of React Native Paper by Callstack yet.
Be the first one to post

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...
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.

Social recommendations and mentions

Based on our record, Google BigQuery should be more popular than React Native Paper by Callstack. 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 Native Paper by Callstack mentions (12)

  • 5 Easy Methods to Implement Dark Mode in React Native
    Several UI libraries are available for React Native developers today. One of the most prominent is React Native Paper, a cross-platform material design for React Native. It is a collection of customizable and production-ready components for React Native, following Google’s Material Design guidelines. With 30+ customizable components, it is a great choice to use with Material UI. - Source: dev.to / 3 months ago
  • Exploring the Best UI Component Libraries for React Native apps
    React Native Paper is a set of customizable and production-ready React Native components based on Google's Material Design specifications. It offers an option for integrating a Babel plugin, thereby minimizing its bundle size by eliminating modules that are not in use. Overall, React Native Paper is a popular choice for developers looking to create aesthetically pleasing user interfaces for React Native... - Source: dev.to / about 1 year ago
  • 7 Popular React Native UI Component Libraries You Should Know
    React Native Paper is a collection of customizable and production-ready components for React Native, following Google’s Material Design guidelines. Global theming support and an optional babel plugin to reduce bundle size are also there. - Source: dev.to / over 2 years ago
  • Is There Something Like Bootstrap (or Responsive design) in React Native?
    Nothing exists that I'm aware of like bootstrap in that sense, especially because people are typically moving away from it. There are UI kits like react-native-paper and Tamagui that exports pre-styled components. Source: over 2 years ago
  • is there a react native equal to MUI for reactjs?
    You don't name what kind of components you want to have all in one lib so I think react native paper is close to MUI visually. Source: over 2 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 / about 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 Native Paper by Callstack and Google BigQuery, you can also consider the following products

NativeBase - Experience the awesomeness of React Native without the pain

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

React Native UI Kitten - Customizable and reusable react-native component kit

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.

Galio - Free and open-source React Native UI built from the ground up as a framework

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.