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Learn MorePros of Kafka
Pros of Kafka Manager
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Pros of Kafka
- High-throughput126
- Distributed119
- Scalable92
- High-Performance86
- Durable66
- Publish-Subscribe38
- Simple-to-use19
- Open source18
- Written in Scala and java. Runs on JVM12
- Message broker + Streaming system9
- KSQL4
- Avro schema integration4
- Robust4
- Suport Multiple clients3
- Extremely good parallelism constructs2
- Partioned, replayable log2
- Simple publisher / multi-subscriber model1
- Fun1
- Flexible1
Pros of Kafka Manager
- Better Insights for Kafka cluster1
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Cons of Kafka
Cons of Kafka Manager
Cons of simplehttp
Cons of Kafka
- Non-Java clients are second-class citizens32
- Needs Zookeeper29
- Operational difficulties9
- Terrible Packaging5
Cons of Kafka Manager
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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.
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’s eye view of the cluster.
What is simplehttp?
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What companies use Kafka Manager?
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What companies use Kafka?
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What tools integrate with Kafka?
What tools integrate with Kafka Manager?
What tools integrate with simplehttp?
What tools integrate with Kafka?
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What are some alternatives to Kafka, Kafka Manager, and simplehttp?
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.
RabbitMQ
RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
Amazon Kinesis
Amazon Kinesis can collect and process hundreds of gigabytes of data per second from hundreds of thousands of sources, allowing you to easily write applications that process information in real-time, from sources such as web site click-streams, marketing and financial information, manufacturing instrumentation and social media, and operational logs and metering data.
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Akka
Akka is a toolkit and runtime for building highly concurrent, distributed, and resilient message-driven applications on the JVM.