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Eclipse RAP VS Apache Kylin

Compare Eclipse RAP VS Apache Kylin and see what are their differences

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

Eclipse RAP logo Eclipse RAP

Java Web Frameworks

Apache Kylin logo Apache Kylin

OLAP Engine for Big Data
  • Eclipse RAP Landing page
    Landing page //
    2020-02-01
  • Apache Kylin Landing page
    Landing page //
    2023-06-29

Eclipse RAP features and specs

  • Cross-Platform Support
    Eclipse RAP allows developers to create web applications that are accessible on various platforms without changing the codebase. This is achieved by rendering the application in a web browser, enabling users on any operating system to access the application seamlessly.
  • Single Codebase
    With Eclipse RAP, developers can maintain a single codebase for both desktop and web applications. This reduces the complexity and resources needed for maintaining separate versions of an application.
  • Rich User Interface
    Eclipse RAP offers a rich set of widgets and tools for creating complex, interactive user interfaces which resemble native desktop applications, enhancing the user experience on web platforms.
  • Integration with Eclipse Ecosystem
    Being part of the Eclipse ecosystem, RAP can easily integrate with other Eclipse projects and tools, offering a robust environment for development and extending functionality.
  • Mature Framework
    As a well-established framework that's been around for many years, Eclipse RAP benefits from a wealth of documentation, community support, and continuous improvement.

Possible disadvantages of Eclipse RAP

  • Learning Curve
    For developers not familiar with the Java and SWT (Standard Widget Toolkit) frameworks, there may be a steep learning curve when adopting Eclipse RAP for the first time.
  • Performance Overheads
    When heavily loading an application with complex UI components, the performance might suffer due to the overhead of rendering traditional desktop functionalities in a web browser.
  • Limited Modern Web Features
    Eclipse RAP might lack some modern web development features or native support for technologies like HTML5 and CSS3 compared to frameworks that are specifically designed for web applications.
  • Dependency on Java
    Since Eclipse RAP is Java-based, it restricts developers to using Java technologies and may not fit into environments where other programming languages or frameworks are preferred.
  • Community Size and Resources
    While it is part of the Eclipse ecosystem, RAP may not have as large a community or as many third-party resources and plugins as other more mainstream web development frameworks.

Apache Kylin features and specs

  • High Query Performance
    Apache Kylin is designed for high-performance, low-latency analytics on large datasets. Its OLAP engine pre-computes and stores aggregated queries, which speeds up query responses significantly.
  • Scalability
    Kylin can handle massive volumes of data, making it suitable for large scale data warehousing needs. It is designed to scale out by distributing the workload across a cluster of servers.
  • Integration with Hadoop Ecosystem
    Kylin integrates seamlessly with the Hadoop ecosystem, leveraging tools like Hive, HBase, and Spark to facilitate data processing and storage, thereby enhancing its functionality and compatibility.
  • Support for Multi-dimensional Analysis
    It provides strong multidimensional analysis capabilities, allowing for complex queries using well-known BI tools like Tableau and Power BI.

Possible disadvantages of Apache Kylin

  • Complex Setup
    Setting up and configuring Apache Kylin can be complex and time-consuming, requiring a deep understanding of the Hadoop ecosystem and its components.
  • Resource Intensity
    The pre-computation of data cubes and their storage can be resource-intensive, consuming significant memory and storage capacity.
  • Limited Flexibility in Querying
    Pre-aggregated cube-based analysis may not cover all ad-hoc queries. Kylin's strength lies in pre-aggregated queries but may fall short in handling highly dynamic, on-the-fly queries.
  • Maintenance Overhead
    Maintaining Kylinโ€™s precomputed cubes can become cumbersome, particularly as data evolves or changes frequently, requiring updates or recalculations of cubes.

Eclipse RAP videos

No Eclipse RAP videos yet. You could help us improve this page by suggesting one.

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Apache Kylin videos

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Extreme OLAP Analytics with Apache Kylin - Big Data Application Meetup

More videos:

  • Review - Apache Kylin: OLAP Cubes for NoSQL Data stores
  • Review - Installing Apache Kylin in Cloudera Quickstart VM Sandbox

Category Popularity

0-100% (relative to Eclipse RAP and Apache Kylin)

Eclipse RAP

Apache Kylin

Developer Tools
100 100%
Developer Tools
0% 0
Databases
0 0%
Databases
100% 100
Web Frameworks
100 100%
Web Frameworks
0% 0
Data Management
0 0%
Data Management
100% 100

User comments

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Social recommendations and mentions

Based on our record, Apache Kylin seems to be more popular. It has been mentiond 1 time 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.

Eclipse RAP mentions (0)

We have not tracked any mentions of Eclipse RAP yet. Tracking of Eclipse RAP recommendations started around Mar 2021.

Apache Kylin mentions (1)

  • Apache Kafka Use Cases: When To Use It & When Not To
    A Kafka-based data integration platform will be a good fit here. The services can add events to different topics in a broker whenever there is a data update. Kafka consumers corresponding to each of the services can monitor these topics and make updates to the data in real-time. It is also possible to create a unified data store through the same integration platform. Developers can implement a unified store either... - Source: dev.to / almost 4 years ago

What are some alternatives?

When comparing Eclipse RAP and Apache Kylin, you can also consider the following products

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

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

Vaadin Framework - Vaadin is a web application framework for Rich Internet Applications (RIA).

Amazon Redshift - Learn about Amazon Redshift cloud data warehouse.

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

Snowflakepowe.red - Snowflake Computing is delivering a data warehouse for the cloud.

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