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What is Yandex Message Queue?

Based on the number of requests processed every second (RPS), users can choose between standard and FIFO (first in, first out) queues. There are familiar tools available to interact with Amazon SQS, such as the HTTP API, the CLI, and various libraries for different programming languages. To boost efficiency, Message Queue employs high-speed NVMe solid-state drives for message storage. Moreover, messages are replicated across multiple geographically diverse availability zones, ensuring reliable storage and reduced latency, along with confirmation of writes. The integration of Message Queue with cloud functions enables the triggering of functions that process messages from the queue. Users can also create a queue to track important metrics, including the count of messages and the duration of calls. Consumers can retrieve messages from a standard queue in any order, granting flexibility in processing. While standard queues guarantee that each message is delivered at least once, there are infrequent cases where a message might be processed more than once. For achieving the best throughput, it is recommended to utilize standard queues, making them particularly suitable for scenarios with high demand. Furthermore, the adaptability of these queues facilitates smooth scaling in response to the evolving requirements of your application, ensuring continued efficiency as it grows.

What is Apache Kafka?

Apache Kafka® is a powerful, open-source solution tailored for distributed streaming applications. It supports the expansion of production clusters to include up to a thousand brokers, enabling the management of trillions of messages each day and overseeing petabytes of data spread over hundreds of thousands of partitions. The architecture offers the capability to effortlessly scale storage and processing resources according to demand. Clusters can be extended across multiple availability zones or interconnected across various geographical locations, ensuring resilience and flexibility. Users can manipulate streams of events through diverse operations such as joins, aggregations, filters, and transformations, all while benefiting from event-time and exactly-once processing assurances. Kafka also includes a Connect interface that facilitates seamless integration with a wide array of event sources and sinks, including but not limited to Postgres, JMS, Elasticsearch, and AWS S3. Furthermore, it allows for the reading, writing, and processing of event streams using numerous programming languages, catering to a broad spectrum of development requirements. This adaptability, combined with its scalability, solidifies Kafka's position as a premier choice for organizations aiming to leverage real-time data streams efficiently. With its extensive ecosystem and community support, Kafka continues to evolve, addressing the needs of modern data-driven enterprises.