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Another approach is that event consumers connect to a message broker that decouples them from event producers. The message broker takes care of managing events, and consumers must subscribe to certain event types so that the broker can make sure that events of this type are delivered to subscribers. In this case, the architecture is much more centered around the delivery broker, and all event producers and consumers are connected to this message broker. In this case, a good technology to consider can be Kafka which is Kafka is highly scalable and resilient.
gRPC is an efficient tunnel-style (RPC) implementation and is well-suited for distributed systems. It has SDKs for many languages and platforms, so it can be used widely, for communication across platforms and languages. gRPC is super fast and efficient because it uses Protocol Buffers (protobufs) to serialize and deserialize, the HTTP/2 standard for optimized binary transfers, and bidirectional streaming to avoid (long) polling and blocking HTTP calls.
For the query style, it’s probably fair to say that GraphQL by now is by far the most popular choice when it comes to building single-page applications (SPAs). It is a language for querying databases from client-side applications. The big advantage that GraphQL has is that it plugs into a JSON-based ecosystem. While GraphQL does not use JSON for queries, it returns results in JSON which make it easy to process in JSON-focused environments.
Nevertheless, the last two mentioned downsides (caching and rate-limiting) can be developed by introducing the API Gateway between the client and data store to win in this situation. For example, an open-source Apache APISIX API Gateway has the matching ability to recognize GraphQL syntax. By efficiently matching GraphQL statements carried in requests, it can filter out abnormal traffic to further apply rate-limiting policies and improve system performance with its caching capability.