event streaming - yibinericxia/documents GitHub Wiki

Data (usually events) streaming send the topic data to all the receivers which subscribe to that topic. A streaming broker stores data in a distributed log file so the subscriber can move backward and forward within the file for data processing. It offers high throughput and high performance for real-time interaction.

Data can be exposed in many formats, such as graph, search, and processed with polyglot persistence. Reactive programming

1. Streaming brokers can deliver the topic to many subscribers without the need for replication
2. Subscribers can be set up to do different things with the same topic data.
3. Streaming brokers always deliver in the same order that topics are queued.

Kafka is a typical event streaming platform consisting of servers and clients via the TCP protocol with events organized and stored in topics. Topics are partitioned so a topic is spread over a number of buckets located on different Kafka brokers.

https://kafka.apache.org/documentation/

Pulsar combines both the traditional messaging queue and streaming for real-time processing.

https://pulsar.apache.org/docs/concepts-architecture-overview/