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Learn MorePros of Kafka
Pros of RedisGreen
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 RedisGreen
- Heroku Add-on1
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Cons of Kafka
Cons of RedisGreen
Cons of Kafka
- Non-Java clients are second-class citizens32
- Needs Zookeeper29
- Operational difficulties9
- Terrible Packaging5
Cons of RedisGreen
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33
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- No public GitHub repository available -
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 RedisGreen?
Redis drives the best sites on the web, from Twitter to Pinterest. RedisGreen makes it easy for anyone to use. Customers can spin up databases at the click of a button. RedisGreen's future is in very fast tools to make the most difficult aspects of modern web application development faster, cheaper, and less labor-intensive.<br>
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What companies use Kafka?
What companies use RedisGreen?
What companies use Kafka?
What companies use RedisGreen?
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What tools integrate with Kafka?
What tools integrate with RedisGreen?
What tools integrate with Kafka?
What tools integrate with RedisGreen?
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What are some alternatives to Kafka and RedisGreen?
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.