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Hibernate vs Kafka: What are the differences?

Hibernate: Idiomatic persistence for Java and relational databases. Hibernate is a suite of open source projects around domain models. The flagship project is Hibernate ORM, the Object Relational Mapper; Kafka: Distributed, fault tolerant, high throughput pub-sub messaging system. Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

Hibernate and Kafka are primarily classified as "Object Relational Mapper (ORM)" and "Message Queue" tools respectively.

"Easy ORM" is the primary reason why developers consider Hibernate over the competitors, whereas "High-throughput" was stated as the key factor in picking Kafka.

Kafka is an open source tool with 12.5K GitHub stars and 6.7K GitHub forks. Here's a link to Kafka's open source repository on GitHub.

Slack, Shopify, and SendGrid are some of the popular companies that use Kafka, whereas Hibernate is used by Bodybuilding.com, StyleShare Inc., and Peewah. Kafka has a broader approval, being mentioned in 501 company stacks & 451 developers stacks; compared to Hibernate, which is listed in 85 company stacks and 72 developer stacks.

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What is Hibernate?

Hibernate is a suite of open source projects around domain models. The flagship project is Hibernate ORM, the Object Relational Mapper.

What is Kafka?

Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
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    What are some alternatives to Hibernate and Kafka?
    MyBatis
    It is a first class persistence framework with support for custom SQL, stored procedures and advanced mappings. It eliminates almost all of the JDBC code and manual setting of parameters and retrieval of results. It can use simple XML or Annotations for configuration and map primitives, Map interfaces and Java POJOs (Plain Old Java Objects) to database records.
    Spring
    A key element of Spring is infrastructural support at the application level: Spring focuses on the "plumbing" of enterprise applications so that teams can focus on application-level business logic, without unnecessary ties to specific deployment environments.
    Sequelize
    Sequelize is a promise-based ORM for Node.js and io.js. It supports the dialects PostgreSQL, MySQL, MariaDB, SQLite and MSSQL and features solid transaction support, relations, read replication and more.
    SQLAlchemy
    SQLAlchemy is the Python SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL.
    Doctrine 2
    Doctrine 2 sits on top of a powerful database abstraction layer (DBAL). One of its key features is the option to write database queries in a proprietary object oriented SQL dialect called Doctrine Query Language (DQL), inspired by Hibernates HQL.
    See all alternatives
    Decisions about Hibernate and Kafka
    Conor Myhrvold
    Conor Myhrvold
    Tech Brand Mgr, Office of CTO at Uber · | 5 upvotes · 127.3K views
    atUber TechnologiesUber Technologies
    Kafka Manager
    Kafka Manager
    Kafka
    Kafka
    GitHub
    GitHub
    Apache Spark
    Apache Spark
    Hadoop
    Hadoop

    Why we built Marmaray, an open source generic data ingestion and dispersal framework and library for Apache Hadoop :

    Built and designed by our Hadoop Platform team, Marmaray is a plug-in-based framework built on top of the Hadoop ecosystem. Users can add support to ingest data from any source and disperse to any sink leveraging the use of Apache Spark . The name, Marmaray, comes from a tunnel in Turkey connecting Europe and Asia. Similarly, we envisioned Marmaray within Uber as a pipeline connecting data from any source to any sink depending on customer preference:

    https://eng.uber.com/marmaray-hadoop-ingestion-open-source/

    (Direct GitHub repo: https://github.com/uber/marmaray Kafka Kafka Manager )

    See more
    Roman Bulgakov
    Roman Bulgakov
    Senior Back-End Developer, Software Architect at Chemondis GmbH · | 3 upvotes · 10.5K views
    Kafka
    Kafka

    I use Kafka because it has almost infinite scaleability in terms of processing events (could be scaled to process hundreds of thousands of events), great monitoring (all sorts of metrics are exposed via JMX).

    Downsides of using Kafka are: - you have to deal with Zookeeper - you have to implement advanced routing yourself (compared to RabbitMQ it has no advanced routing)

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    RabbitMQ
    RabbitMQ
    Kafka
    Kafka

    The question for which Message Queue to use mentioned "availability, distributed, scalability, and monitoring". I don't think that this excludes many options already. I does not sound like you would take advantage of Kafka's strengths (replayability, based on an even sourcing architecture). You could pick one of the AMQP options.

    I would recommend the RabbitMQ message broker, which not only implements the AMQP standard 0.9.1 (it can support 1.x or other protocols as well) but has also several very useful extensions built in. It ticks the boxes you mentioned and on top you will get a very flexible system, that allows you to build the architecture, pick the options and trade-offs that suite your case best.

    For more information about RabbitMQ, please have a look at the linked markdown I assembled. The second half explains many configuration options. It also contains links to managed hosting and to libraries (though it is missing Python's - which should be Puka, I assume).

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    Frédéric MARAND
    Frédéric MARAND
    Core Developer at OSInet · | 2 upvotes · 92.5K views
    atOSInetOSInet
    RabbitMQ
    RabbitMQ
    Beanstalkd
    Beanstalkd
    Kafka
    Kafka

    I used Kafka originally because it was mandated as part of the top-level IT requirements at a Fortune 500 client. What I found was that it was orders of magnitude more complex ...and powerful than my daily Beanstalkd , and far more flexible, resilient, and manageable than RabbitMQ.

    So for any case where utmost flexibility and resilience are part of the deal, I would use Kafka again. But due to the complexities involved, for any time where this level of scalability is not required, I would probably just use Beanstalkd for its simplicity.

    I tend to find RabbitMQ to be in an uncomfortable middle place between these two extremities.

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    Interest over time
    Reviews of Hibernate and Kafka
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    How developers use Hibernate and Kafka
    Avatar of Pinterest
    Pinterest uses KafkaKafka

    http://media.tumblr.com/d319bd2624d20c8a81f77127d3c878d0/tumblr_inline_nanyv6GCKl1s1gqll.png

    Front-end messages are logged to Kafka by our API and application servers. We have batch processing (on the middle-left) and real-time processing (on the middle-right) pipelines to process the experiment data. For batch processing, after daily raw log get to s3, we start our nightly experiment workflow to figure out experiment users groups and experiment metrics. We use our in-house workflow management system Pinball to manage the dependencies of all these MapReduce jobs.

    Avatar of Kang Hyeon Ku
    Kang Hyeon Ku uses HibernateHibernate

    Mybatis 로 쿼리를 만들고 조건분 분기식 for 문을 쿼리에 달아 더이상 쿼리를 알아 볼 수 없게 되었을때 이게 의마가 있나 싶었다. 그 때 한번 orm 을 써보면 어떨까 싶어 최근에 배우기 시작한 orm 이다. 정말 편하게 개발을 할 수 있는데 일조하고 있다. 다만 결국에 쿼리를 날려 맵핑을 하는데, 쿼리를 잘 모르거나 그에 대한 지식 없이 쓰다가는 망하겠구나 하는 생각이 많이 들었다.

    Avatar of Analytical Informatics
    Analytical Informatics uses HibernateHibernate

    We use a Clojure-powered wrapper around Hibernate to provide an ORM access to our data store for applications, as well as offering SSO integration and HIPAA logging functionality.

    Avatar of Coolfront Technologies
    Coolfront Technologies uses KafkaKafka

    Building out real-time streaming server to present data insights to Coolfront Mobile customers and internal sales and marketing teams.

    Avatar of Tongliang Liu
    Tongliang Liu uses HibernateHibernate

    Can't escape from when you're on the Java stack and deal with relational db.

    Avatar of Satoru Ishikawa
    Satoru Ishikawa uses HibernateHibernate

    Strut や Spring など Java web app flame work での Object Relation Mapperとして

    Avatar of icarus-dave
    icarus-dave uses HibernateHibernate

    Persistence layer for backend data; maps entities to the database.

    Avatar of ShareThis
    ShareThis uses KafkaKafka

    We are using Kafka as a message queue to process our widget logs.

    Avatar of Christopher Davison
    Christopher Davison uses KafkaKafka

    Used for communications and triggering jobs across ETL systems

    Avatar of theskyinflames
    theskyinflames uses KafkaKafka

    Used as a integration middleware by messaging interchanging.

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