Apache kafka is one of the well known open-source data processing systems available with over 50 thousand companies using it. It has a market share of more than 26.7% currently. These numbers indicate the popularity of this distributed data store which makes it unique for optimized real-time streaming with speed and efficiency.
Apache Kafka is an open-source distributed streaming platform that lets developers build real-time event driven applications, as users prefer real-time experiences from apps. It has the ability to handle large streams of data and process them efficiently.
Because of this ability, it is the ideal underlying infrastructure for apps and pipelines that manage these types of data. Furthermore, Apache kafka’s architecture acts as both a message broker and a storage unit that enables real-time experiences across different application types.
For example: streaming Netflix, browsing LinkedIn.
How Does Apache Kafka Work
Apache kafka is designed around a partitioned log model that combines two traditional messaging ways – queue and publish subscribe to reduce limitations. Logs are divided into partitions which enable users to share processing and also allow multiple subscribers to use the same data stream. This facilitates scalability, multi-subscriber support and replayability which lets applications consume data at their own speed. Coming to the process, here’s how it works.
- Data flows into kafka from various sources and
- Producers send the data to their respective destinations.
- Kafka brokers systematically sort, store and control these data flows.
- Consumers receive the messages.
- Topics are folders that classify where messages should go.
- Then partitions help in dividing the load so kafka can process huge amounts of data promptly.
Features of Apache Kafka
Apache kafka started as a LinkedIn project and is an open-source system managed by the Apache Software Foundation. At present, companies like IBM, Cloudera and Confluent also contribute and play a significant role in building Kafka. Let us take a closer look at why Apache Kafka is important.
Distributed and Fault Tolerant
Kafka’s architecture ensures consistent availability by distributing data across various brokers, maintaining service even during hardware failures which makes it tolerant to faults and reliable.
Highly Scalable
Kafka’s horizontal scalability lets companies to scale effortlessly by adding brokers and ensure cost-efficient infrastructure growth while supporting increasing customer demand and big data processing.
Maximum Performance
Kafka manages millions of messages per second which meets the needs of enterprises that manage global and critical apps with unmatched speed and efficiency.
Real-time Efficiency
Kafka’s low latency makes it perfect for time-sensitive situations like financial transactions, custom recommendations, IoT monitoring and user experience improvements.
Global Trust
With adoption by 60% of fortune 100 companies, Kafka is trusted as the standard solution for real-time data streaming needs.
Use Cases of Apache Kafka
Here are some of the use cases of Apache Kafka:
- Data Ingestion – To collect metrics from various locations at scale.
- Event streaming – To stream process events.
- Messaging – It can be used as a messaging system.
- Real time analytics – To capture and add changes from the database in real-time and track websites activity and click stream analysis
Conclusion
Apache kafka has become a backbone of modern data streaming with its speed, efficiency and reliability. Its versatility across industries highlights its critical role in powering modern digital ecosystems
FAQ’s
What are the core components of Apache Kafka?
There are 5 components of Apache kafka which are.
- Kafka broker – It consists of multiple brokers that work together for scalability, fault tolerance.
- Producer – An application that sends messages to kafka topics.
- Topic – It is a category or type to which messages are published.
- Consumer – It is an application that reads messages from kafka topics.
- Zookeeper – It is a management component that handles metadata, leader election and broker co-ordination, enabling controlled access to kafka resources.
Is Apache Kafka a database?
Apache Kafka is a real-time event streaming platform and not a database.
Which language is used in Apache Kafka?
It is an open-source system which was developed by the Apache Software Foundation written in Java and Scala.
What is the maximum message size in Apache Kafka?
Apache Kafka default maximum message size is 1 MB, this limit is designed to help brokers manage memory effectively.
