Apache Druid: Choosing a System for Large-Scale Data Analysis
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Title: Some Like it Hot: Choosing a System for Large-Scale Data Analysis
Talk abstract: Apache Druid is a modern cloud-native, stream-native, analytics database designed for workflows where fast queries and instant ingest are important. Druid excels at instant data visibility, ad-hoc queries, operational analytics, and handling high concurrency. It is a strong candidate for being the workhorse system for hot analytics.
There is no shortage of systems that claim to help with the analysis of large amounts of data. Under the hood, today's popular systems have a variety of interesting and unique architectures. In this talk, we'll reflect on why you can never seem to find that single perfect system, and how to evaluate the capabilities of various systems through the prism of a temperature-based spectrum of use cases, from cold to hot analytics.
Speaker Bio: Rachel Pedreschi is the VP of Community at Imply. A "Data Geek-ette”, Rachel is no stranger to the world of high-performance databases and data warehouses. She is a Vertica, Informix and Redbrick certified DBA on top of her work with Cassandra and has 20+ years of business intelligence and ETL tool experience. Rachel has an MBA from San Francisco State University and a BA in Mathematics from University of California, Santa Cruz.
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Apache Druid: Choosing a System for Large-Scale Data Analysis