Kafka Cloud Databases

Apache Kafka is a distributed messaging system for real-time communication between server applications — a Data Bus. It implements a «publish-subscribe» model where applications can publish messages to specific topics, and other applications can subscribe to these topics to receive messages.

Key advantages of using Apache Kafka include:

— Ability to scale horizontally, allowing it to handle large amounts of data.

— High performance: Kafka is optimized for high throughput and low latency.

— Real-time stream processing, ensuring timely event awareness.

— Seamless integration with various systems such as databases, data warehouses, and stream processing systems.

— Ability to serve as a centralized repository for large amounts of data, functioning as an organization’s unified data store.

Topics group messages by themes. Users subscribe to topics created by producers. This allows them to view messages within that topic. For each topic, Apache Kafka maintains a message log, which can be divided into several partitions.

A partition consists of all the messages within a topic, ordered from newest to oldest. This structure allows users to see the most recent messages first within a topic.

Kafka helps solve various tasks such as:

— Collecting and aggregating events or logs from different sources (e.g., Clickstream).
— Simultaneous event delivery to multiple consumers. This feature is beneficial in scenarios where an event needs to be processed by several systems or services at the same time.
— Building Event-Sourcing or Event-Driven Systems. In such systems, events are stored in Kafka and used to update the local databases of microservices.
— Stream processing: In this case, Kafka serves as an intermediary storage for streaming data from one system to another.

Currently, this functionality is not available, but our team is working on its implementation in the future.