Running real-time data-intensive applications on Apache Hadoop requires complex architectures to store and query data, typically involving multiple independent systems that are tied together through custom-engineered pipelines. A common pattern is to use a NoSQL engine like Apache HBase for caching and later transformations, the results of which are periodically written to HDFS in one of the popular open columnar... Read More

The Cloudera Impala project is pioneering the next generation of Hadoop capabilities: the convergence of fast SQL queries with the capacity, scalability, and flexibility of a Hadoop cluster. With Impala, the academic and Hadoop communities now have an open-sourced codebase that helps query data stored in HDFS and Apache HBase in real time, using familiar SQL syntax. In contrast with... Read More

On-line transaction processing (OLTP) is one of the two most important enterprise data management applications. Transaction processing workloads typically exhibit high concurrency and provide ample opportunities for parallel execution by multicore hardware. Unfortunately, due to the characteristics of the application, transaction processing systems must moderate and coordinate communication between independent agents. As a result, transaction processing systems cannot always convert... Read More