Exam Professional Data Engineer topic 1 question 155 discussion

A I think it's the only technology that met the requirements

vote for A: topics, offsets --> apache kafka

Only Kafka can support publish/subscribe semantics on hundreds of topics

Ability to Seek to a Particular Offset: Kafka allows consumers to seek to a specific offset in a topic, enabling you to read data from a specific point, including back to the start of all data ever captured. This is a fundamental capability of Kafka. Support for Publish/Subscribe Semantics: Kafka supports publish/subscribe semantics through topics. You can have hundreds of topics in Kafka, and consumers can subscribe to these topics to receive messages in a publish/subscribe fashion. Retain Per-Key Ordering: Kafka retains the order of messages within a partition. If you have a key associated with your messages, you can ensure per-key ordering by sending messages with the same key to the same partition. Scalability: Kafka is designed to handle high-throughput data streaming and is capable of scaling to meet your needs. Apache Kafka aligns well with the requirements you've outlined for centralized data ingestion and delivery. It's a robust choice for scenarios that involve data streaming, publish/subscribe, and retaining message ordering.

Answer A: Apache Kafka Key words: Ingestion and Delivery together ( it is combination of pub/sub for ingestion, and delivery = dataflow+any database in gcp) Offset of a topic = Partition of a topic and reprocess specific part of topic, its not possible in pub/sub as it is designed for as come and go for 1 topic. Per key ordering. means message with same key can be process or assigned to a user in kafka.

deberia ser la C, debido a que siempre es mejor escoger los servicios de google