Carpenter Jeff, Hewitt Eben. Cassandra: The Definitive Guide: Distributed Date at Web Scale

Revised 3rd Edition. — DataStax version. — O’Reilly, 2022. — 432 p. — ISBN 978-1-492-09775-4.Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you'll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This revised third edition--updated for Cassandra 4.0 and new developments in the Cassandra ecosystem, including deployments in Kubernetes with K8ssandra--provides technical details and practical examples to help you put this database to work in a production environment. Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra's nonrelational design, with special attention to data modeling. Developers, DBAs, and application architects looking to solve a database scaling issue or future-proof an application will learn how to harness Cassandra's speed and flexibility. Understand Cassandra's distributed and decentralized structure Use the Cassandra Query Language (CQL) and cqlsh (the CQL shell) Create a working data model and compare it with an equivalent relational model Design and develop applications using client drivers Explore cluster topology and learn how nodes exchange data Maintain a high level of performance in your cluster Deploy Cassandra onsite, in the cloud, or with Docker and Kubernetes Integrate Cassandra with Spark, Kafka, Elasticsearch, Solr, and LuceneThis book will assist readers to:
Understand Cassandra's distributed and decentralized structure
Use the Cassandra Query Language (CQL) and cqlish, the CQL shell
Create a working data model and compare it with an equivalent relational model
Develop sample applications using client drivers for languages including Java, Python, and Node.js
Explore cluster topology and learn how nodes exchange data
Maintain a high level of performance within a cluster
Deploy Cassandra on site, in the Cloud, or with Docker
Integrate Cassandra with Spark, Hadoop, Elasticsearch, Solr, and Lucene