Wildfire: HTAP for Big Data

Ronald Barber, Vijayshankar Raman, Richard Sidle, Yuanyuan Tian, Pinar Tözün

Publikation: Konference artikel i Proceeding eller bog/rapport kapitelEncyclopædiartikelForskningpeer review


Emerging large-scale real-time analytic applications (real-time inventory/pricing /recommendations, fraud detection, risk analysis, IoT, etc.) require data management systems that can handle fast transactions (OLTP) and analytics (OLAP) simultaneously. Some of them even require analytical queries as part of a transaction. Efficient processing of transactional and analytical requests, however, leads to different design decisions in a system. This article presents the Wildfire system, which targets hybrid transactional and analytical processing (HTAP) for big data. Wildfire leverages Apache Spark to enable large-scale data processing with different types of complex analytical requests and columnar data processing to enable fast transactions and analytics concurrently.
TitelEncyclopedia of Big Data Technologies
ISBN (Elektronisk)978-3-319-63962-8
StatusUdgivet - 2019


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