Best Alternative Hosted Message Queue Service
What is a Message Queue?
A message queue is a part of messaging processing systems that allows data interchange between independent applications and services. Message queues preserve "messages" (packets of data created by applications for consumption by other applications) in the order they are transmitted until the consuming application can process them. It allows messages to securely wait until the recipient application is ready, ensuring that messages in queue are not discarded in the event of a network or receiving application failure.
This approach, referred to as asynchronous messaging, avoids data loss and allows systems to continue operating in the case of process or connection failure. It enables developers to isolate processes and applications, ensuring that their connections are self-contained and event-driven, thus increasing the architecture's reliability.
Message queues are offered in various deployment choices for messaging systems, including specialized physical devices, cloud solutions, supercomputers, and software.
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Table of contents
Why use Message Queues
Message queuing systems are extensively used across sectors and may provide developers and network administrators with a variety of advantages, including the following:
- Reliable message delivery: Using a message queue guarantees that Business communications between apps are not lost and are sent to the intended recipient just once. Further de-duplication or loss-prevention logic is redundant with this functionality in place.
- Inter-application connectivity: Certain message queue systems provide encryption, transnationality, and other communication elements between applications and services. This streamlines application development and allows the coexistence of different systems.
- Flexibility: Message queue solutions are available in various languages, including Java, Node.js, COBOL, C/C++, Go,.NET, Python, Ruby, and C#. Additionally, they may handle multiple application programming interfaces (APIs) and protocols, namely MQTT, AMQP, and REST.
- Resilience: Asynchronous messaging eliminates the effect of application-specific failures on the system. If one component of the system becomes unresponsive, the other components may continue to communicate with the queue and process messages. This reduces the likelihood that the failure of a single element will jeopardize the stability of the whole system.
- Increased security: A message queue may be capable of identifying and authenticating all communications, and in specific message queue systems, messages may be encrypted at rest, in transit, or end-to-end. This may add to the application's and infrastructure's overall security.
- Integrated file transfers: Certain message queue systems incorporate extra capabilities, such as file transfer. Organizations may use this in place of FTP that already has such systems.
Case studies
Enterprise computer infrastructures are becoming more complicated and dispersed. By offering a single, resilient, secure, shared communications backbone, messaging integrates applications and services across different platforms. It prevents data loss and guarantees that systems continue to operate even when the connection is unreliable.
Message queues are unmatched in their ability to integrate on-premises backend systems with cloud services. Cloud designs often decompose applications into tiny, self-contained components, simplifying their design, development and performance management. Message queues allow communication between these decoupled cloud-based apps and on-premises systems.
Message queuing improves the architecture's robustness by allowing for persistent messages. It implies that they are written to disk until the service that received the message verifies its processing. We may utilize messaging queues in situations requiring high confidentiality, fault tolerance, and accuracy, such as financial transaction processing, airline reservation, or healthcare patient record updates.
Additionally, we may utilize message queues to allow communication between applications and systems running on various clouds (public or private), even if they are situated in different nations or even on faraway continents. Utilizing a message queue improves fault tolerance and may be used to avoid data duplication or loss across geographically and technically disjointed systems. Because each service in the system is detached from the others conceptually, it may continue to operate even if other services or applications fail or stall.
Message queues are compatible with various applications, including mobile, IoT, and conventional transaction system records. Additionally, they support multiple platforms, including virtual machines and containers, and may facilitate integration between older applications and cutting-edge solutions.
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Top Message queue services
Here, we've analyzed some of the most popular message queue services:
IronMQ
IronMQ is a hosted message queue that is enormously scalable. It simplifies data and event management inside your application by supporting numerous clients and a managed environment that relieves you of server management responsibilities, enabling you to concentrate on your application.
The messaging system provides a uniform mechanism for component and service applications to communicate. It is a highly available service that is steadfast in its execution, on-time delivery, and no latency delay. It is the most popular choice among organizations since it allows for cloud-native solutions for today's trendy application architecture.
IronMQ offers a message queuing solution for distributed cloud applications, enabling message delivery inside and across systems through pushing and pulling queues. The queue automatically sends messages to a single (unicast) or multiple (multicast) endpoints using the push technique. The pull method delivers messages at intervals, and subscribing endpoints retrieve them from the queue.
IronMQ also supports extended polling, enabling developers to maintain a connection to a queue open indefinitely until a message becomes available. Support for pushing and pulling queues ensures that messages are sent to other systems more quickly, while the lengthy polling period helps avoid empty replies.
Apache Kafka – High-Performance Queue Broker
Kafka is an open-source messaging system that serves as a highly scalable queue broker. It is a distributed event streaming technology capable of processing a large number of messages. Kafka messages are saved on disk, enabling the smooth transmission of messages from one place to another. Messages are duplicated throughout the whole Kafka cluster to avoid undesirable actions such as data loss. Kafka is a messaging technology designed for real-time event streaming, data pipelining, and replaying for rapid, scalable processes.
Thousands of businesses rely on Apache Kafka's distributed message queue software for high-performance data pipelines and its interaction with Apache Storm and Spark. Apache Kafka is a messaging system that we can use in place of several corporate messaging systems. LinkedIn created it as an internal messaging system capable of handling 1.4 trillion messages per day. It is the optimal and most appropriate platform for implementing Queues due to the speed increase provided by sequential disk I/O operations. Additionally, it is an excellent option for significant data use cases because of its ability to achieve high throughput with minimal resources, i.e., millions of messages per second.
RabbitMQ – Application-Oriented Messaging
RabbitMQ is the most extensively deployed and widely used open-source message broker software – a messaging intermediate. It is developed in Erlang and is supported by the Pivotal Software Foundation. It provides a standard platform for your apps and a secure environment for sending and receiving messages. Performance, dependability, high availability, clustering, and federation are only some of the characteristics. Moreover, it has an intuitive administration UI for monitoring and controlling your message broker.
You can download RabbitMQ message broker or queue manager for all major operating systems, including Linux, Windows, and macOS, from the official website.
It is suggested to utilize RabbitMQ plugins to alleviate message brokers' workloads and extend their capabilities. The most critical RabbitMQ plugin is the management plugin, which must be manually activated. The RabbitMQ management plugin enables users to administer RabbitMQ through a user interface. It assists in examining various messaging statistics and maintains a picture of all actions involving data in queues.
Celery – Task Queue Distributed
Celery is an open-source, scalable, and dependable distributed message queuing system designed to handle massive quantities of data. It is a task queue that prioritizes real-time processing while still allowing for job scheduling. Celery is distributed under the terms of the BSD License. Celery uses distributed message forwarding to implement a primary asynchronous process queue or job queue. The execution units or process tasks are performed simultaneously on a single or more worker node using multiprocessing, eventlet, or gevent. Celery jobs may be executed asynchronously or synchronously.
Celery is built in Python, although the protocol is portable to any language. Celery is used to handle millions of jobs per day in production systems such as Instagram. Additionally, webhooks enable it to interact with different programming languages. A PHP client, a Go client, a Node.js client, and a Ruby client named RCelery are all available.
Nsq — Distributed Real-Time Messaging
NSQ is a free and open-source real-time distributed memory best message queue optimized for scalability. It is built in the Go programming language and scales to billions of messages each day. NSQ's message structure is distributed and decentralized. Its features exclude the possibility of a single point failure. It provides fault tolerance and high availability, as well as fast message delivery.
NSQ is a mature product that is simple to set up and performs well. The command line specifies all setup and deployment settings, and the generated binaries have no runtime dependencies. For optimum flexibility, the data format of NSQ messages may be JSON, MsgPack, Protocol Buffers, or anything else. It comes with official Go and Python libraries and a bunch of new additional client libraries. NSQ comprises three critical components: nsqd, nsqlookupd, and nsqadmin.
Radisson — Java Service in a Distributed Environment
Radisson is the most sophisticated and user-friendly Redis Java client with In-Memory data grid capabilities. Because Radisson is a fundamental, easy-to-use, and message queue monitoring tool, you do not need to be familiar with any Redis commands to get started setting it. Distributed applications on the Java platform must use Redis-based objects, collections, locks, synchronizers, and services. Parallel execution of Java task services and Redis-based distributed implementations through the ExecutorService and ScheduledExecutorService is possible.
Conclusion
We addressed message queuing, its applications, advantages, and the most popular message queue services across various programming languages. There are many open-source and closed-source messaging systems, and more are developed to address the scheduling issues that engineers encounter.
If you’re interested in using IronMQ, sign up for the free trial here. IronMQ is a low cost alternative MQ service, and you can also access it via the Heroku add-on.
It is critical to learn the advantages and disadvantages of various tools and then choose one appropriate for your requirements. When you have a cloud-agnostic message queue service with an easy-to-use dashboard and superior security, you can increase the efficiency of your business application.
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