SQL on Big Data

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Discover various commercial and open-source products that execute SQL on Big Data platforms, gaining insights into the architectures of SQL engines and their internal workings regarding execution, data movement, latency, scalability, performance, and system requirements. This resource consolidates solutions to challenges related to speed, scalability, and diverse operations required for data integration and SQL tasks. It begins with a historical overview of SQL on Big Data, then delves into the products, architectures, and innovations in this rapidly evolving field. The discussion includes the advancements in performance, scalability, and the ability to manage different data types. The text covers SQL on Big Data engines' impact on OLTP, OLAP, operational analytics, and emerging HTAP systems. Key topics include: **Batch Architectures**—the evolution of the Hive engine for improved query latency; **Interactive Architectures**—designs that support low latency for large datasets; **Streaming Architectures**—architectures enabling queries on real-time data using in-memory structures; **Operational Architectures**—supporting transactions on Big Data platforms; and **Innovative Architectures**—exploring new SQL engines with groundbreaking concepts. This resource is ideal for business analysts, BI engineers, developers, data scientists, architects, and quality assurance professionals.