Best Message Queue Systems

Message queue software is an asynchronous communication middleware that connects applications. Traditional monolithic software is built to communicate with itself or a few other applications. When the software sends or receives data from another software, this data is called a message. It is difficult to send and receive data to another app due to different operating systems, network protocols, and programming languages. Message queue software solves these problems by handling messages for applications from different environments. It creates a new high availability, high reliability, high throughput, and low latency environment to send and receive messages from one application to another. 

As the name suggests, MQ software lines up different messages by “queue” and processes each message through standardized methods. This helps companies to develop high-performance cloud services and apps such as microservices that can communicate with other applications and operating systems without worrying about compatibility issues. 

In the early years, big companies invested heavily in proprietary software and middleware that could connect their products with each other. Using the same IT stacks and standards, these companies can create connected applications. With the vast network of applications connected by middleware, users can solve various complex problems that require multiple inputs and outputs from different environments. 

However, only big companies with big budgets can afford to develop this approach. For most companies and non-business users who use different network standards, programming languages, and data structures, connected applications seem to be unobtainable. This is why there are many business issues that seem to be easy to solve but are technically challenging to implement. For example, hospitals and insurance companies can’t share patient data automatically because their applications aren’t compatible in communicating with each other. Those who managed to set up the connectivity may still use proprietary protocols such as raw UDP, TCP, and HTTP, which are hard to scale and integrate with other applications. 

To solve this issue, early open-source organizations build open source message brokers specific to a language environment like Java and Python. Later big companies began building their own messaging system for others, such as AWS and IBM MQ, to create enterprise messaging platforms that run on their own IT systems. Software buyers can select the best message queue web services or on-premises software to connect various assets such as big data servers to the internet of things (IoT).

What Does MQ Stand For?

MQ stands for Message Queue. A “message” is data that transfers from one party to another. A “queue” is how that message is transferred and processed from one party to another.

The following are some core features within Message Queue Software that can help users ensure high availability of message queuing services:

Message query: MQ allows applications to query messages by ID, topics, keys, and contents. This enables the user to organize messages based on custom rules.

Message tracing: MQ can trace routing information from the producer of the message to the consumer. This allows users to analyze metadata on the message producer and consumer for network performance issues. 

Dead-letter queue: MQ supports dead-letter queues (DLQ) to save messages that can’t be processed for debugging to determine why the queueing process failed. 

Message blocklist and allowlist: MQ supports account-based blocklist and allowlist policies to authorize or unauthorize messages from internal and external parties. 

Multiple message processes: Message queue processes can be created for different models. In a peer-to-peer model, a producer sends one message to one consumer. In a pub/sub model, producers can send group messages to consumers with the same cluster ID. In RPC (request/reply) model, MQ can load balance messages back and forth between producer and consumer. 

Dashboard: A user-friendly dashboard can visualize comprehensive and multidimensional metrics of message product and consumption based on clusters, topics, instances, and groups. This will spot trends for server resource allocation and security improvement. 

Monitoring and alerting: Messaging activities can be monitored in real time, and alerts can be sent to notify the IT and data team to resolve issues in a timely manner.

Decoupling: Message queue tools decouple (separate) applications and message services. This simplifies CI/CD development so developers can design and update core components without worrying about the message components. 

Load shifting: Messages can automatically be queued according to their size, frequency, and quantity. When there is a large number of message requests, servers can fail to process this amount of volume. It will either crash or indiscriminately reject all incoming messages. Without load shifting, message disruption will halt online business operations and negatively affect revenue. 

Scalability: MQ servers can be integrated with other applications and be allocated an appropriate amount of resources based on needs. This saves users time from manually changing the message process during disruptions or software upgrades.