Ebook: Cassandra: The Definitive Guide, (Revised) Third Edition: Distributed Data at Web Scale
Author: Jeff Carpenter Eben Hewitt
- Genre: Computers // Databases
- Tags: Security, NoSQL, Distributed Systems, Monitoring, Logging, Microservices, Queries, Application Development, Kubernetes, Performance Tuning, Data Modeling, K8ssandra, Cassandra, CQL
- Year: 2022
- Publisher: O'Reilly Media
- City: Sebastopol, CA
- Edition: 3
- Language: English
- pdf
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 Lucene
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 Lucene
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