Stream Processing

Delta Lake To the Rescue

Reading Time: 4 minutes Welcome Back. In our previous blogs, we tried to get some insights about Spark RDDs and also tried to explore some new things in Spark 2.4. You can go through those blogs here: RDDs – The backbone of Apache Spark Spark 2.4: Adding a little more Spark to your code In this blog, we will be discussing something called a Delta Lake. But first, let’s Continue Reading

Flinkathon: What makes Flink better than Kafka Streams?

Reading Time: 2 minutes Initially, I would like you all to focus on a few questions before comparing the frameworks:1. Is there any comparison or similarity between Flink and the Kafka?2. What could be better in Flink over the Kafka?3. Is it the problem or system requirement to use one over the other? Before talking about the Flink betterment and use cases over the Kafka, let’s first understand their Continue Reading

Kafka Streams : More Than Just a Dumb Storage

Reading Time: 5 minutes Whenever we hear the word Kafka, all we think about it as a messaging system with a publisher-subscriber model that we use for our streaming applications as a source and a sink. So we can say that Kafka is just a dumb storage system that stores the data provided by a producer for a long time (configurable) and it can provide it to some consumer whenever Continue Reading

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