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Название: High-Performance Data Architectures: How to Maximize Your Business with a Cloud-Based Database
Автор: Joe McKendrick, Ed Huang
Издательство: O’Reilly Media, Inc.
Год: 2023-08-04
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.2 MB
By choosing the right database, you can maximize your business potential, improve performance, increase efficiency, and gain a competitive edge. This insightful report examines the benefits of using a simplified data architecture containing cloud-based HTAP (hybrid transactional and analytical processing) database capabilities. You'll learn how this data architecture can help data engineers and data decision makers focus on what matters most: growing your business. Relational databases helped in discovering and understanding trends within the business but were expensive in terms of multiuser or per-processor licensing, as well as difficult to set up and maintain. SQL itself required a robust understanding of its structure and commands. Seeking to avoid the complexity of building SQL-based queries for relational databases, along with their restrictions, a new breed of databases emerged: not only SQL (NoSQL) databases. The first generation of NoSQL databases focused on key-value stores (Berkeley DB and similar), text searching (Elasticsearch), and later document stores such as CouchDB and MongoDB.
Автор: Joe McKendrick, Ed Huang
Издательство: O’Reilly Media, Inc.
Год: 2023-08-04
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.2 MB
By choosing the right database, you can maximize your business potential, improve performance, increase efficiency, and gain a competitive edge. This insightful report examines the benefits of using a simplified data architecture containing cloud-based HTAP (hybrid transactional and analytical processing) database capabilities. You'll learn how this data architecture can help data engineers and data decision makers focus on what matters most: growing your business. Relational databases helped in discovering and understanding trends within the business but were expensive in terms of multiuser or per-processor licensing, as well as difficult to set up and maintain. SQL itself required a robust understanding of its structure and commands. Seeking to avoid the complexity of building SQL-based queries for relational databases, along with their restrictions, a new breed of databases emerged: not only SQL (NoSQL) databases. The first generation of NoSQL databases focused on key-value stores (Berkeley DB and similar), text searching (Elasticsearch), and later document stores such as CouchDB and MongoDB.