The Kafka ecosystem comprises of various tools and technologies that integrate with Kafka to extend its functionality and provide solutions catering to specific use cases.
Kafka Streams is a powerful library for building real-time event streaming applications in Apache Kafka. It simplifies the development of stateful stream processing applications, by providing a simple and easy-to-use foundation set of APIs that allows developers to write streaming applications using the same constructs as batch processing.
It allows developers to perform a wide variety of stream processing operations, from filtering and transformation to complex aggregations and joins, in real-time. It is tightly integrated with Kafka’s partitioning and replication features, which allows for scalable and fault-tolerant stream processing.
Kafka Streams also supports windowing operations, which enables developers to perform calculations over time-based (e.g., sliding, tumbling) or session-based (i.e., unlimited and bounded) windows. Additionally, Kafka Streams provides a range of built-in serializers and deserializers to cover the most common data formats, and it also allows for custom serialisation.
Kafka Connect is a scalable and fault-tolerant tool for streaming data between external systems and Apache Kafka. It simplifies the process of integrating Kafka with other data sources, such as databases, filesystems, and message queues, by providing a simple configuration-based framework for creating and managing connectors.
Kafka Connect is built on a distributed, fault-tolerant architecture, which allows it to scale horizontally and handle high-throughput data ingestion independently of Kafka brokers. It also features a REST API for configuring and monitoring connectors, and it provides a range of pre-built connectors for popular data sources, such as JDBC, Elasticsearch, and HDFS.
Kafka REST Proxy
Kafka REST Proxy is a RESTful interface that allows external systems to interact with Apache Kafka using an HTTP/HTTPS protocol. It sits between client applications and Kafka clusters and translates HTTP requests into Kafka-native protocols such as Producer and Consumer.
Kafka REST Proxy simplifies the process of integrating Kafka with web-based or cloud-native applications by providing a simple, standardised API for publishing or consuming Kafka messages. It supports a range of message formats, including Avro, JSON, and binary data, and provides built-in support for schema registry.
By using Kafka REST Proxy, client applications can easily interact with Kafka from any programming languages or platforms that support HTTP. It also provides an additional layer of security by enforcing access control policies and enabling secure communication over HTTPS. Developers can also gain expose to Kafka in a more familiar format via RESTful interfaces.
Schema Registry is a tool for managing schemas in Apache Kafka that provides a centralised store for schema files. It enables producers and consumers to agree on a standardised format for the data being sent or received from the Kafka cluster. This helps to ensure interoperability between different applications and enables developers to evolve data schemas over time without breaking existing data pipelines.
Schema Registry supports multiple schema formats such as JSON, Avro or Protobuf, and stores schema information in a schema registry topic on the Kafka broker. When publishing or consuming messages, the schema information is checked and validated against the schema registry topic. If the schema is not compatible, the producer or consumer can be notified with an error message.
ksqlDB is a powerful open-source database built on top of Apache Kafka that provides a SQL-like interface for real-time stream processing. It simplifies the process of building real-time, event-driven applications by enabling developers to write queries and transformations using a familiar SQL syntax.
ksqlDB allows developers to create tables, define schemas, and perform complex aggregations and joins on real-time streams of data. It is designed to be scalable and fault-tolerant, and it uses Kafka’s distributed architecture to provide high-throughput data processing. It also integrates seamlessly with Kafka ecosystem components such as Kafka Connect or Kafka Streams.
However, be warned that there are some limitations and nuances to be aware of when compared to SQL.
An end-to-end suite of solutions for Kafka developers which includes Kafka management, testing, monitoring, data quality, and data governance. It allows developers to interact with the entire Kafka ecosystem such as Brokers, Topics, Consumers, Producers, Kafka Connect, and Confluent Schema Registry.
An exciting new open source project that aims to leverage well established Kafka design principles to help the Data Mesh community.