Apache Kafka

Apache Kafka isn’t a traditional relational or NoSQL database, but it can function as a database for streaming data. By storing events durably, enabling replay, and supporting real-time processing through Kafka Streams and ksqlDB, Kafka is ideal for event sourcing, data pipelines, and microservices communication. However, it’s not suited for transactional workloads, long-term archival, or general-purpose CRUD operations. The best approach is to use Kafka alongside open-source databases like PostgreSQL, ClickHouse, Redis, or TimescaleDB to build modern, scalable data infrastructures that balance real-time event streaming with persistent storage.

In today’s fast-paced digital world, businesses need to process and analyze data in real-time to stay competitive. Apache Kafka has emerged as a leading solution for high-throughput, real-time data streaming, enabling organizations to handle massive volumes of data with ease. In this blog post, we’ll dive deep into what makes Kafka a game-changer, its key features, use cases, and how it compares to other data streaming platforms. What is Apache Kafka? Apache Kafka is an open-source distributed event streaming platform designed to handle real-time data feeds with high throughput and low latency. Originally developed by LinkedIn, Kafka has become the backbone of many modern data architectures, powering real-time analytics, event-driven applications, and data integration pipelines. ...