Building a Real-Time Streaming ETL Pipeline in 20 Minutes
There has been a lot of talk recently that traditional ETL is dead. In the traditional ETL paradigm, data warehouses were king, ETL jobs were batch-driven, everything talked to everything
There has been a lot of talk recently that traditional ETL is dead. In the traditional ETL paradigm, data warehouses were king, ETL jobs were batch-driven, everything talked to everything
We are very excited for the GA for Kafka release 0.11.0.0 which is just days away. This release is bringing many new features as described in the previous Log Compaction
In this blog post, we’re going to get back to basics and walk through how to get started using Apache Kafka with your Python applications. We will assume some basic
In his book Design Patterns Explained, Alan Shalloway compares his car to an umbrella. After all, he uses both to stay dry in the rain. The umbrella has an advantage
For many, microservices are built on a protocol of requests and responses. REST etc. This approach is very natural. It is after all the way we write programs: we make
We are very excited to share a wealth of streaming news from the past month! If you are looking for an ideal streaming data service that delivers the resilient, scalable
Introduction What’s great about the Kafka Streams API is not just how fast your application can process data with it, but also how fast you can get up and running
Kafka Summit New York City was the largest gathering of the Apache Kafka community outside Silicon Valley in history. Over 500 “Kafkateers” from 400+ companies and 20 countries converged in
Apache Kafka® is the best enterprise streaming platform that runs straight off the shelf. Just point your client applications at your Kafka cluster and Kafka takes care of the rest:
Today, I’m really excited to announce Confluent CloudTM, Apache Kafka® as a Service: the simplest, fastest, most robust and cost effective way to run Apache Kafka in the public cloud.
Use CL60BLOG to get an additional $60 of free Confluent Cloud