Many people promise fast data as the next step after big data. The idea of creating a complete end-to-end data pipeline that combines Spark, Akka, Cassandra, Kafka, and Apache Mesos came up two years ago, sometimes called the SMACK stack. The SMACK stack is an ideal environment for handling all sorts of data-processing needs which can be nightly batch-processing tasks, real-time ingestion of senso
Google Cloud Dataflow is a next generation managed big data service based on the Apache Beam programming model. It provides a unified model for batch and streaming data processing, with an optimized execution engine that automatically scales based on workload. Customers report being able to build complex data pipelines more quickly using Cloud Dataflow compared to other technologies like Spark, an
Change data capture is a hot topic. Debezium’s goal is to make change data capture easy for multiple DBMSes, but admittedly we’re still a young open source project and so far we’ve only released a connector for MySQL with a connector for MongoDB that’s just around the corner. So it’s great to see how others are using and implementing change data capture. In this post, we’ll review Yelp’s approach
This document provides an overview of Twitter Heron, an open source real-time streaming engine developed by Twitter to replace Storm. It describes Heron's design goals of improved performance, predictability, manageability and developer productivity. The architecture is outlined, including task isolation for easier debugging. Back pressure is discussed as a way to handle stragglers. Load shedding
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