![]() They unfortunately cannot abstract away all complexity - such as the need for each participant to know the location of all others in order to connect to them, or complex failure scenarios that you don’t generally have to deal with in brokered systems (e.g., the case where a participant dies mid-fanout). So, if you’re building a new application or unsatisfied with a current one that uses Pub/Sub, consider Redis Streams if what you need is “Pub/Sub, but with the ability to resume on disconnection without losing messages.” Pros and consīrokerless tools are the fastest communication methodology you can think of, even faster than Redis Pub/Sub. Since Streams was not available before Redis version 5, some people opted to use Pub/Sub in situations where they would have preferred better delivery guarantees, and are now making the switch. As you can imagine, this has implications in performance (there’s no such thing as a free lunch after all), but reliable delivery does apply to a wider range of use cases. RabbitMQ defaults to the former behavior while Redis Pub/Sub focuses on just doing the bare minimum amount of work for fire-and-forget. ![]() The difference is not just in persistence, but in the general idea of reliable delivery (i.e., application level acks) vs. You can still use tools with persistence like NATS or RabbitMQ for this use case, as they do allow you to turn off persistence, but the only pure synchronous messaging broker that I know of is Redis. In this category, Redis Pub/Sub stands alone as far as I know. While this architecture is usually described as star-shaped, with the broker being the center of the star, the broker itself can be (and often is) a clustered system. Brokeredīrokered means that participants connect to the same service, which acts, as the name suggests, as a central broker to implement the whole message-routing mechanism. They are rightfully described as “TCP sockets on steroids.” In practice, you import the library into your code and use it to instantiate a connection that can employ various built-in message routing mechanisms, such as Pub/Sub, Push/Pull, Dealer/Router, etc. In this category, we have libraries such as ZeroMQ and the more recent nanoMsg. Brokerlessīrokerless means that participants are still connected directly but have the option of employing a different pattern than RPC. At that point, you have two main options: brokerless or brokered tools. And while the RPC paradigm works well for one-to-one communication, you will occasionally need to support one-to-many or many-to-many. These services only do graceful degradation because for more sensitive use cases (e.g., a payment service asking an order service to start processing a paid order), other asynchronous mechanisms I’ll describe below are more common. For example, Netflix’s “watch next” section could display a random sample of shows if the recommendation service was unreachable. If Service B went offline, Service A would not be able to communicate with B, and so A would need to implement an internal failure recovery procedure, which most of the time means doing graceful degradation. The simplest form is Service A and Service B doing direct remote procedure calls (RPC), by invoking Service B’s HTTP REST endpoint from Service A, for example. In this context, synchronous means that all parties need to be active at the same time to be able to communicate. Finally, I’ll leave you with a small take-away that will hopefully help you build better solutions faster. In this article, I will guide you through the defining characteristics of various communication patterns, and I’ll briefly introduce the most popular tools used to implement each. With the introduction of Streams in Redis, we now have another communication pattern to consider in addition to Redis Pub/Sub and other tools like Kafka and RabbitMQ. Let’s talk about communication tools and patterns.
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