|godsend||251.46 kB||MIT||6 Years||8 Jun 2017|
|journaly||8.06 kB||MIT||4 Years||6 Dec 2022|
|redis-smq||56.72 kB||MIT||6 Years||26 Mar 2023|
|redis-smq-common||21.34 kB||MIT||1 Years||25 Mar 2023|
|@event-inc/connections||23.09 kB||MIT||Less than one year||11 Sep 2023|
|redis-smq-monitor-client||231.79 kB||MIT||1 Years||4 May 2023|
|@buildable/connections||10.1 kB||MIT||Less than one year||10 Feb 2023|
|godsend-basics||6.68 kB||MIT||6 Years||8 Jun 2017|
|querator||7.64 kB||MIT||1 Years||15 Nov 2022|
|godsend-extras||5.71 kB||MIT||6 Years||8 Jun 2017|
|pubs-js||4.99 kB||MIT||3 Years||24 Feb 2020|
|redis-smq-monitor||49.9 kB||MIT||4 Years||4 May 2023|
|@buildable/pipelines||10.39 kB||MIT||Less than one year||10 Feb 2023|
|hermes-queue||14.79 kB||MIT||Less than one year||3 Mar 2023|
|@anzerr/atium.broker||9.1 kB||MIT||4 Years||21 Jan 2022|
In a complex application ecosystem, communication between different services can be a challenging hurdle. This is where Message Broker libraries shine by acting as an intermediary for such communication. Here are a few instances when they prove instrumental:
Decoupling systems: Instead of having microservices communicate directly, which can get messy with the application's scaling, a message broker can serve as the central communication hub, effectively decoupling the systems.
Fault tolerance: Message brokers can store messages temporarily when the recipient service is down, ensuring there is no data loss in case of system failures.
Load balancing: In cases of peak load, instead of overwhelming a message recipient all at once, a message broker can queue the messages, gradually feeding them in manageable capacities.
Real-time processing: If your application requires real-time processing, then message broker libraries provide a method of allowing data to be processed as it comes in.
While message broker libraries might differ slightly based on their individual attributes, they generally provide some standard functionalities detailed below:
Asynchronous messaging: One of the main features of message brokers is their ability to handle asynchronous communications effectively.
Queueing: Most message broker libraries provide message queuing capabilities, where messages are stored until the recipient is ready to process them.
Topic exchange: This is essentially a filtering mechanism that enables a message to be routed to multiple queues and subscribers based on their topic of interest.
Message transformation: This functionality pertains to adapting the message structure to suit the requirements of the recipient.
Publish/subscribe model: This is a popular method of communication where a message is not sent to a specific recipient but rather dispatched to all subscribers interested in the message type.
Complex setup and maintenance: Some message brokers may require a complex setup, and they would need continual monitoring and maintenance to ensure optimal performance.
Overhead cost: While they do offer great utility, message brokers inherently add an overhead cost to the system in terms of response time.
Data duplication: It's essential to be mindful that data can be duplicated in a broker system when multiple consumers are subscribed to the same topic or queue, which could lead to data inconsistency.
Dependency on libraries: The chosen message broker library would typically require a specific client library to interact with.
Always test thoroughly to ensure that the package you're importing works as expected, contributes positively to your application and doesn't add unnecessary code or operational burden.