The backbone your data pipelines have been waiting for.
Kafka isn’t just a buzzword—it’s the backbone your data pipelines have been waiting for. Who new that messaging system, like Apache Kafka should hold a central place in a Data Engineer toolbelt. Apache Kafka is a low-latency distributed data streaming platform for real-time data processing. Kafka can handle large volumes of data and is very helpful for distributed data integration projects. Top 2 reasons why you might need Kafka in your Data Integration architecture 1. Support multiple destinations by decoupling data producers and data consumers. Data in source will be processed only once, which lowers an overall cost in consumption-based data producer databases and we can add new/change existing destinations without changing the extraction components. 2. Ability to deal with massive amounts of data , supports high throughput and scalability. Decoupling pipeline extract and load stages is an important Data Integration principle and can improve pipeline flexibility, extract and loa...