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ActiveMQ
ActiveMQ

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ActiveMQ vs Hadoop: What are the differences?

Developers describe ActiveMQ as "A message broker written in Java together with a full JMS client". Apache ActiveMQ is fast, supports many Cross Language Clients and Protocols, comes with easy to use Enterprise Integration Patterns and many advanced features while fully supporting JMS 1.1 and J2EE 1.4. Apache ActiveMQ is released under the Apache 2.0 License. On the other hand, Hadoop is detailed as "Open-source software for reliable, scalable, distributed computing". The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.

ActiveMQ and Hadoop are primarily classified as "Message Queue" and "Databases" tools respectively.

"Open source" is the top reason why over 9 developers like ActiveMQ, while over 34 developers mention "Great ecosystem" as the leading cause for choosing Hadoop.

ActiveMQ and Hadoop are both open source tools. It seems that Hadoop with 9.27K GitHub stars and 5.78K forks on GitHub has more adoption than ActiveMQ with 1.51K GitHub stars and 1.05K GitHub forks.

According to the StackShare community, Hadoop has a broader approval, being mentioned in 237 company stacks & 127 developers stacks; compared to ActiveMQ, which is listed in 33 company stacks and 17 developer stacks.

What is ActiveMQ?

Apache ActiveMQ is fast, supports many Cross Language Clients and Protocols, comes with easy to use Enterprise Integration Patterns and many advanced features while fully supporting JMS 1.1 and J2EE 1.4. Apache ActiveMQ is released under the Apache 2.0 License.

What is Hadoop?

The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
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Why do developers choose ActiveMQ?
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      Jobs that mention ActiveMQ and Hadoop as a desired skillset
      PinterestPinterest
      San Francisco, CA; Palo Alto, CA
      PinterestPinterest
      San Francisco, CA; Palo Alto, CA
      PinterestPinterest
      San Francisco, CA; Palo Alto, CA
      PinterestPinterest
      San Francisco, CA; Palo Alto, CA
      What companies use ActiveMQ?
      What companies use Hadoop?

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      What tools integrate with ActiveMQ?
      What tools integrate with Hadoop?

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      What are some alternatives to ActiveMQ and Hadoop?
      RabbitMQ
      RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
      Kafka
      Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
      Apollo
      Build a universal GraphQL API on top of your existing REST APIs, so you can ship new application features fast without waiting on backend changes.
      Amazon SQS
      Transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be always available. With SQS, you can offload the administrative burden of operating and scaling a highly available messaging cluster, while paying a low price for only what you use.
      Celery
      Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well.
      See all alternatives
      Decisions about ActiveMQ and Hadoop
      StackShare Editors
      StackShare Editors
      Apache Thrift
      Apache Thrift
      Kotlin
      Kotlin
      Presto
      Presto
      HHVM (HipHop Virtual Machine)
      HHVM (HipHop Virtual Machine)
      gRPC
      gRPC
      Kubernetes
      Kubernetes
      Apache Spark
      Apache Spark
      Airflow
      Airflow
      Terraform
      Terraform
      Hadoop
      Hadoop
      Swift
      Swift
      Hack
      Hack
      Memcached
      Memcached
      Consul
      Consul
      Chef
      Chef
      Prometheus
      Prometheus

      Since the beginning, Cal Henderson has been the CTO of Slack. Earlier this year, he commented on a Quora question summarizing their current stack.

      Apps
      • Web: a mix of JavaScript/ES6 and React.
      • Desktop: And Electron to ship it as a desktop application.
      • Android: a mix of Java and Kotlin.
      • iOS: written in a mix of Objective C and Swift.
      Backend
      • The core application and the API written in PHP/Hack that runs on HHVM.
      • The data is stored in MySQL using Vitess.
      • Caching is done using Memcached and MCRouter.
      • The search service takes help from SolrCloud, with various Java services.
      • The messaging system uses WebSockets with many services in Java and Go.
      • Load balancing is done using HAproxy with Consul for configuration.
      • Most services talk to each other over gRPC,
      • Some Thrift and JSON-over-HTTP
      • Voice and video calling service was built in Elixir.
      Data warehouse
      • Built using open source tools including Presto, Spark, Airflow, Hadoop and Kafka.
      Etc
      See more
      Interest over time
      Reviews of ActiveMQ and Hadoop
      No reviews found
      How developers use ActiveMQ and Hadoop
      Avatar of Pinterest
      Pinterest uses HadoopHadoop

      The MapReduce workflow starts to process experiment data nightly when data of the previous day is copied over from Kafka. At this time, all the raw log requests are transformed into meaningful experiment results and in-depth analysis. To populate experiment data for the dashboard, we have around 50 jobs running to do all the calculations and transforms of data.

      Avatar of Yelp
      Yelp uses HadoopHadoop

      in 2009 we open sourced mrjob, which allows any engineer to write a MapReduce job without contending for resources. We’re only limited by the amount of machines in an Amazon data center (which is an issue we’ve rarely encountered).

      Avatar of Pinterest
      Pinterest uses HadoopHadoop

      The massive volume of discovery data that powers Pinterest and enables people to save Pins, create boards and follow other users, is generated through daily Hadoop jobs...

      Avatar of Casey Smith
      Casey Smith uses ActiveMQActiveMQ

      Remote broker and local client for incoming data feeds. Local broker for republishing data feeds to other systems.

      Avatar of Robert Brown
      Robert Brown uses HadoopHadoop

      Importing/Exporting data, interpreting results. Possible integration with SAS

      Avatar of Rohith Nandakumar
      Rohith Nandakumar uses HadoopHadoop

      TBD. Good to have I think. Analytics on loads of data, recommendations?

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