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Disque
Disque

8
17
+ 1
0
Kafka Manager
Kafka Manager

38
45
+ 1
0
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Disque vs Kafka Manager: What are the differences?

Developers describe Disque as "In-memory, distributed job queue". Disque is an ongoing experiment to build a distributed, in-memory, message broker. Its goal is to capture the essence of the "Redis as a jobs queue" use case, which is usually implemented using blocking list operations, and move it into an ad-hoc, self-contained, scalable, and fault tolerant design, with simple to understand properties and guarantees, but still resembling Redis in terms of simplicity, performance, and implementation as a C non-blocking networked server. On the other hand, Kafka Manager is detailed as "A tool for managing Apache Kafka, developed by Yahoo". This interface makes it easier to identify topics which are unevenly distributed across the cluster or have partition leaders unevenly distributed across the cluster. It supports management of multiple clusters, preferred replica election, replica re-assignment, and topic creation. It is also great for getting a quick bird鈥檚 eye view of the cluster.

Disque and Kafka Manager can be categorized as "Message Queue" tools.

Disque and Kafka Manager are both open source tools. It seems that Kafka Manager with 7.55K GitHub stars and 1.84K forks on GitHub has more adoption than Disque with 7.37K GitHub stars and 516 GitHub forks.

What is Disque?

Disque is an ongoing experiment to build a distributed, in-memory, message broker. Its goal is to capture the essence of the "Redis as a jobs queue" use case, which is usually implemented using blocking list operations, and move it into an ad-hoc, self-contained, scalable, and fault tolerant design, with simple to understand properties and guarantees, but still resembling Redis in terms of simplicity, performance, and implementation as a C non-blocking networked server.

What is Kafka Manager?

This interface makes it easier to identify topics which are unevenly distributed across the cluster or have partition leaders unevenly distributed across the cluster. It supports management of multiple clusters, preferred replica election, replica re-assignment, and topic creation. It is also great for getting a quick bird鈥檚 eye view of the cluster.
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            What are some alternatives to Disque and Kafka Manager?
            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.
            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.
            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.
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            Decisions about Disque and Kafka Manager
            Conor Myhrvold
            Conor Myhrvold
            Tech Brand Mgr, Office of CTO at Uber | 4 upvotes 98.3K 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 )

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