Apache kafka is part of Hadoop which is an open source process and this software was developed by the foundation Apache Software and it is basically written in Java and Scala. And the aim of the project is to get the high throughput and a very low latency platform for the purpose of handling all the real-time data and feeds that it get.
Kafka can connect the external systems easily with the help of the Kafka connects which will be providing a stream of Kafka that is the library for all the Java processing.
And it is mainly influenced by transactional logs.
Kafka is a part of the Hadoop and has various Kafka use cases.
The Kafka connect API is nothing but just a framework used for the purpose of importing and exporting all the data from the other systems.
This thing was added in the Kafka version 0.9.0.0 and uses the API internally for the producer and the consumer.
The framework for the connect executes everything itself with the “connectors” then actual logic will be implemented to read or write the same in the system.
Kafka apache stream is a library stream processing that takes place in Java. And this thing is added to the Kafka version 0.10.0.0.
This does a very good job by allowing all the development from the library through the stream processing in the stateful manner which includes the things like scalability, elastic and full fletched tolerance.
This is the main API which allows all the DSL stream processing which offers the high-level operations filtering, mapping, grouping, windows, aggregations, joinings and all the notions that are present in a table.
This a very important thing in the Kafka architecture. Until the version of Kafka 0.9x for which the brokers of the Kafka are only adaptable with this version or with the older clients only.
After which Kafka version 0.10.0.0 came up the brokers made it adaptable by only the new clients.
In this case, if the older client meets with the newer brokers then the features of that are provided by the brokers can be accessed.
Latest Kafka apache techniques have a very vast and extensive integration into the infrastructures that are in enterprise-level. And this becomes a very important aspect for keeping a check on the performance done by Kafka in the scale.
Keeping a check on everything and the performance requires metric for tracking from the brokers, the consumers, and the producer, which is also an addition to the ZooKeeper which is basically used for maintaining a coordination between the consumers.