DistributedLog聽vs聽Kafka Manager

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DistributedLog
DistributedLog

12
27
+ 1
0
Kafka Manager
Kafka Manager

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

What is DistributedLog? High-performance replicated log service, by Twitter. DistributedLog (DL) is a high-performance, replicated log service, offering durability, replication and strong consistency as essentials for building reliable distributed systems.

What is Kafka Manager? 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.

DistributedLog and Kafka Manager can be primarily classified as "Message Queue" tools.

Some of the features offered by DistributedLog are:

  • High Performance
  • Durable and Consistent
  • Efficient Fan-in and Fan-out

On the other hand, Kafka Manager provides the following key features:

  • Manage multiple clusters
  • Easy inspection of cluster state (topics, brokers, replica distribution, partition distribution)
  • Run preferred replica election

DistributedLog 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 DistributedLog with 2.25K GitHub stars and 283 GitHub forks.

What is DistributedLog?

DistributedLog (DL) is a high-performance, replicated log service, offering durability, replication and strong consistency as essentials for building reliable distributed systems.

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 DistributedLog and Kafka Manager?
            Kafka
            Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
            RabbitMQ
            RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
            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 DistributedLog and Kafka Manager
            Conor Myhrvold
            Conor Myhrvold
            Tech Brand Mgr, Office of CTO at Uber | 4 upvotes 98.9K 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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