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Javalin VS Apache Hive

Compare Javalin VS Apache Hive and see what are their differences

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Javalin logo Javalin

Simple REST APIs for Java and Kotlin

Apache Hive logo Apache Hive

Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.
  • Javalin Landing page
    Landing page //
    2022-10-26
  • Apache Hive Landing page
    Landing page //
    2023-01-13

Javalin features and specs

  • Lightweight
    Javalin is a lightweight framework with minimal dependencies, making it easy to integrate into existing projects and reducing overhead.
  • Simplicity
    The framework is simple to use and has a straightforward API, which makes it easier for developers to understand and work with.
  • Kotlin & Java Support
    Javalin natively supports both Kotlin and Java, making it flexible for projects written in either language.
  • WebSocket Support
    It includes built-in support for WebSockets, enabling real-time communication between the client and server without additional dependencies.
  • Extensive Documentation
    Javalin comes with comprehensive documentation and guides, which help developers get up to speed quickly.

Possible disadvantages of Javalin

  • Limited Features
    As a minimalist framework, Javalin may lack some advanced features present in more comprehensive frameworks, requiring additional implementations from developers.
  • Community Support
    While growing, the community around Javalin is not as large as other established frameworks, which may result in fewer resources or third-party libraries.
  • Performance Overhead
    Though lightweight, Javalin may not offer the same level of performance optimization as frameworks specifically designed for high-performance use cases.
  • Limited Middleware
    Compared to other frameworks, the middleware support in Javalin is more limited, potentially requiring additional code for customization.

Apache Hive features and specs

  • Scalability
    Apache Hive is built on top of Hadoop, allowing it to efficiently handle large datasets by distributing the load across a cluster of machines.
  • SQL-like Interface
    Hive provides a familiar SQL-like querying language, HiveQL, which makes it easier for users with SQL knowledge to perform data analysis on large datasets without needing to learn a new syntax.
  • Integration with Hadoop Ecosystem
    Hive integrates seamlessly with other components of the Hadoop ecosystem such as HDFS for storage and MapReduce for processing, making it a versatile tool for big data processing.
  • Schema on Read
    Hive uses a schema-on-read model which allows it to work with flexible data schemas and handle unstructured or semi-structured data efficiently.
  • Extensibility
    Users can extend Hive's capabilities by writing custom UDFs (User Defined Functions), UDAFs (User Defined Aggregate Functions), and SerDes (Serializers/ Deserializers).

Possible disadvantages of Apache Hive

  • Latency in Query Processing
    Queries in Hive often take longer to execute compared to traditional databases, as they are converted to MapReduce jobs which can introduce significant latency.
  • Limited Real-time Processing
    Hive is designed for batch processing and is not suitable for real-time analytics due to its reliance on MapReduce, which is not optimized for low-latency operations.
  • Complex Configuration
    Setting up Hive and configuring it to work optimally within a Hadoop cluster can be complex and require a significant amount of effort and expertise.
  • Lack of Support for Transactions
    Hive does not natively support full ACID transactions, which can be a limitation for applications that require consistent transaction management across large datasets.
  • Dependency on Hadoop
    Hive's reliance on the Hadoop ecosystem means it inherits some of Hadoop's limitations, such as a steep learning curve and the need for substantial resources to manage a cluster.

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Apache Hive videos

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Hive vs Impala - Comparing Apache Hive vs Apache Impala

Category Popularity

0-100% (relative to Javalin and Apache Hive)

Javalin

Apache Hive

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

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Social recommendations and mentions

Based on our record, Javalin should be more popular than Apache Hive. It has been mentiond 36 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.

Javalin mentions (36)

  • Year After Switching from Java to Go: Our Experiences
    But Javas has so many of these web frameworks?! * Spring (https://spring.io/) * Spring Boot (https://spring.io/projects/spring-boot) * Helidon (https://helidon.io/) * Micronaut (https://micronaut.io/) * Quarkus (https://quarkus.io/) * JHipster (https://www.jhipster.tech/) * Vaadin (https://vaadin.com/) That's just to mention the bigger ones, there's lots of mini frameworks like Javalin (https://javalin.io/) and... - Source: Hacker News / 3 months ago
  • Latudio – a language acquisition app with a listening-oriented approach
    - like Sentences exercise, but you can select your own set of sentences. You can also set goals and view statistics about your progress. None of this would be possible without the great help from hundreds of our contributors [3], who translated, mapped and recorded content. All the content you find in the app was reviewed multiple times by several people and recordings are made by native speakers. No story in the... - Source: Hacker News / 5 months ago
  • Show HN: Donobu – Mac App for Web Automation and Testing
    - Javalin 6 for the web framework (https://javalin.io/). - Source: Hacker News / 7 months ago
  • Spark – A web micro framework for Java and Kotlin
    I'd recommend Javalin (https://javalin.io/) instead. Same idea, only executed better and it is actively maintained. - Source: Hacker News / about 1 year ago
  • Spark – A web micro framework for Java and Kotlin
    SparkJava has an actively developed fork/successor called Javalin[1]. It's straightforward to convert from SparkJava to Javalin. The latter is written in Kotlin, but works fine with ordinary Java. While the rest of the Java world was devolving into annotation hell, AOP and other nightmares, these Java microframeworks showcased what happens when you forego legacy Java and leverage modern Java language features... - Source: Hacker News / about 1 year ago
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Apache Hive mentions (8)

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What are some alternatives?

When comparing Javalin and Apache Hive, you can also consider the following products

Spark Framework - Spark Framework is a simple and lightweight Java web framework built for rapid development.

ClickHouse - ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.

vert.x - From Wikipedia, the free encyclopedia

Apache Doris - Apache Doris is an open-source real-time data warehouse for big data analytics.

Micronaut Framework - Build modular easily testable microservice & serverless apps

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

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