Why choose RocketMQ
Why RocketMQ
During the early stages of RocketMQ’s development at Alibaba, we utilized it for a multitude of purposes, including asynchronous communications, search, social networking activity flows, data pipelines, and trade processes. As our trade business grew, we noticed that the messaging cluster was under increasing pressure.
After observing and analyzing the performance of the ActiveMQ IO module, we identified a bottleneck as the number of queues and virtual topics increased. We attempted to address this issue through various methods, such as throttling, circuit breakers, and service downgrades, but none proved satisfactory. We also considered using Kafka, a popular messaging solution, but it did not meet our requirements for low latency and high reliability, as explained below. As a result, we made the decision to develop a new messaging engine capable of handling a wider range of use cases, from traditional pub/sub to high-volume, real-time, zero-error transaction systems.
Since its inception, Apache RocketMQ has been widely adopted by enterprise developers and cloud vendors due to its simple architecture, rich business functionality, and extreme scalability. After more than a decade of extensive scenario polishing, RocketMQ has become the industry standard for financial-grade reliable business messages and is widely used in Internet, big data, mobile Internet, IoT, and other fields.
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The following table shows the comparison between RocketMQ, ActiveMQ and Kafka
RocketMQ vs. ActiveMQ vs. Kafka
Messaging Product | Client SDK | Protocol and Specification | Ordered Message | Scheduled Message | Batched Message | BroadCast Message | Message Filter | Server Triggered Redelivery | Message Storage | Message Retroactive | Message Priority | High Availability and Failover | Message Track | Configuration | Management and Operation Tools |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ActiveMQ | Java, .NET, C++ etc. | Push model, support OpenWire, STOMP, AMQP, MQTT, JMS | Exclusive Consumer or Exclusive Queues can ensure ordering | Supported | Not Supported | Supported | Supported | Not Supported | Supports very fast persistence using JDBC along with a high performance journal,such as levelDB, kahaDB | Supported | Supported | Supported, depending on storage,if using levelDB it requires a ZooKeeper server | Not Supported | The default configuration is low level, user need to optimize the configuration parameters | Supported |
Kafka | Java, Scala etc. | Pull model, support TCP | Ensure ordering of messages within a partition | Not Supported | Supported, with async producer | Not Supported | Supported, you can use Kafka Streams to filter messages | Not Supported | High performance file storage | Supported offset indicate | Not Supported | Supported, requires a ZooKeeper server | Not Supported | Kafka uses key-value pairs format for configuration. These values can be supplied either from a file or programmatically. | Supported, use terminal command to expose core metrics |
RocketMQ | Java, C++, Go | Pull model, support TCP, JMS, OpenMessaging | Ensure strict ordering of messages,and can scale out gracefully | Supported | Supported, with sync mode to avoid message loss | Supported | Supported, property filter expressions based on SQL92 | Supported | High performance and low latency file storage | Supported timestamp and offset two indicates | Not Supported | Supported, Master-Slave model, without another kit | Supported | Work out of box,user only need to pay attention to a few configurations | Supported, rich web and terminal command to expose core metrics |