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React Native UI Kitten VS Google Cloud Dataflow

Compare React Native UI Kitten VS Google Cloud Dataflow and see what are their differences

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React Native UI Kitten logo React Native UI Kitten

Customizable and reusable react-native component kit

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.
  • React Native UI Kitten Landing page
    Landing page //
    2022-10-12
  • Google Cloud Dataflow Landing page
    Landing page //
    2023-10-03

React Native UI Kitten features and specs

  • Customizable Theme
    React Native UI Kitten offers a customizable theme that allows developers to easily adjust the design according to their app's branding needs. This flexibility is facilitated through default themes and the ability to create custom themes that can be applied across the application.
  • Consistency
    With a comprehensive set of UI components, UI Kitten helps maintain design consistency across different parts of the application, ensuring a unified look and feel.
  • Cross-Platform Support
    The library supports both iOS and Android platforms, enabling developers to create apps that work seamlessly across mobile operating systems with a single code base.
  • Community and Documentation
    UI Kitten has an active community and well-documented resources which provide developers support and guidance, facilitating smoother development processes and faster issue resolution.

Possible disadvantages of React Native UI Kitten

  • Size
    Inclusion of a comprehensive UI library can increase the application's bundle size, which might be a concern for performance-conscious developers aiming to keep their apps lightweight.
  • Learning Curve
    Though UI Kitten is relatively intuitive, new developers may face a learning curve to fully utilize its features and customize themes appropriately.
  • Limited Customization Beyond Theme
    While UI Kitten offers robust theming options, further customization of individual components may be limited compared to building components from scratch, potentially requiring additional custom development.
  • Dependency on Eva Design System
    UI Kitten is deeply integrated with the Eva Design System, which might limit flexibility for developers who wish to use or integrate with different design systems.

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.

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.

React Native UI Kitten videos

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

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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

Category Popularity

0-100% (relative to React Native UI Kitten and Google Cloud Dataflow)

React Native UI Kitten

Google Cloud Dataflow

Development Tools
100 100%
Development Tools
0% 0
Big Data
0 0%
Big Data
100% 100
React Native
100 100%
React Native
0% 0
Data Dashboard
0 0%
Data Dashboard
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 Native UI Kitten and Google Cloud Dataflow

React Native UI Kitten Reviews

We have no reviews of React Native UI Kitten yet.
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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

Social recommendations and mentions

Google Cloud Dataflow might be a bit more popular than React Native UI Kitten. We know about 14 links to it since March 2021 and only 12 links to React Native UI Kitten. 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 UI Kitten mentions (12)

  • React Native styling options/libraries
    Https://akveo.github.io/react-native-ui-kitten/ is a good alternative, I especially like their demo app, I can just refer a client to that and ask them what screens they like. Source: about 2 years ago
  • 7 Popular React Native UI Component Libraries You Should Know
    React Native UI Kitten is a React Native implementation of the Eva Design system. It offers a set of general-purpose UI components styled in the same way to take care of visual appearance. There are a lot of standalone components available as well. - Source: dev.to / over 2 years ago
  • Form Validation in React (Native) using Formik
    UI Kitten: UI Kitten is a React Native framework for creating stunning cross-platform mobile applications. It is based on Eva Design System and provides a set of general purpose UI components styled in a similar way. - Source: dev.to / over 2 years ago
  • Building a React Native Filter - Part 1
    In the application we built for the client we had two modal instances, the filtering modal (that used the native modal) and an alert modal (where we used UI Kitten's modal). We like the native modal because it offer's us the possibility of deciding how it transitions and it's easier to set it up fullscreen. - Source: dev.to / over 3 years ago
  • Top React Native UI Component Libraries
    Image source: https://akveo.github.io/react-native-ui-kitten/ React Native UI Kitten – a React Native implementation of the Eva Design system. It offers a set of about 20 general-purpose components styled in the same way to take care of visual appearance. There are a lot of standalone components available as well. The library is based on Eva Design System, containing a set of general-purpose UI components styled... - Source: dev.to / over 3 years ago
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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 2 years ago
  • Here’s a playlist of 7 hours of music I use to focus when I’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: over 2 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: over 2 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: over 2 years ago
  • Why we don’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 3 years ago
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What are some alternatives?

When comparing React Native UI Kitten and Google Cloud Dataflow, you can also consider the following products

NativeBase - Experience the awesomeness of React Native without the pain

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

React Native Paper by Callstack - Material Design for React Native (Android & iOS)

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

Ignite CLI - React Native toolchain with boilerplates, plugins, and more

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

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