Kafka Overview
Apache Kafka is a distributed event streaming platform capable of handling trillions of events a day. It is designed for high-throughput, low-latency, and scalable fault-tolerance, making it the industry standard for real-time data pipelines and streaming applications.
Native Kafka Support in FlowMQ
FlowMQ natively supports the Apache Kafka protocol. This means you can use your favorite Kafka client libraries to connect to FlowMQ and leverage its powerful, distributed architecture for your streaming data needs, without needing a separate Kafka cluster.
Key Features of Kafka
- Distributed Commit Log: Kafka organizes data into topics, which are partitioned and replicated across multiple brokers, providing both scalability and fault tolerance.
- High Throughput: It is capable of processing hundreds of thousands of messages per second.
- Scalability: You can elastically scale your cluster by adding more brokers to handle growing data volumes.
- Durability and Reliability: Messages are persisted to disk and replicated, preventing data loss.
Common Use Cases
Real-Time Data Pipelines
Kafka is often used to build pipelines that reliably get data between systems and applications. It can be used to stream data from various sources into data lakes, databases, or real-time analytics systems.
Event-Driven Architectures
As a backbone for event-driven systems, Kafka allows different microservices to communicate asynchronously by producing and consuming events, decoupling services and improving overall system resilience.
Log Aggregation
Kafka can be used to collect logs from multiple services and make them available in a standard format to various consumers, such as monitoring dashboards, security analysis tools, or long-term storage.
Kafka Client SDKs
To get started with your language of choice, refer to the following guides for connecting to FlowMQ with various Kafka client libraries.