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.
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Jeff Carpenter works in Developer Relations at DataStax, where he uses his background in system architecture, microservices and Apache Cassandra to help empower developers and operations engineers to build distributed systems that are scalable, reliable, and secure. Jeff has worked on large-scale systems in the defense and hospitality industries and is co-author of Cassandra: The Definitive Guide. Eben Hewitt is the CTO and Chief Architect at Sabre Hospitality where he is responsible for the technology strategy and for designing large-scale, mission-critical systems and leading teams to build them. He has served as CTO at one of the world's largest hotel companies and CIO of O'Reilly Media. He has been a consultant to Warburg Pincus and others on distributed data and a frequent speaker at international conferences. He is the author of several books, including Technology Strategy Patterns (2018), Cassandra: The Definitive Guide, Java SOA Cookbook, and several other books on architecture, web and software development, including Semantic Software Design (2019). He's won several innovation awards for his software design work.
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Paperback. Condition: New. 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 structureUse the Cassandra Query Language (CQL) and cqlsh (the CQL shell)Create a working data model and compare it with an equivalent relational modelDesign and develop applications using client driversExplore cluster topology and learn how nodes exchange dataMaintain a high level of performance in your clusterDeploy Cassandra onsite, in the cloud, or with Docker and KubernetesIntegrate Cassandra with Spark, Kafka, Elasticsearch, Solr, and Lucene. Seller Inventory # LU-9781492097143
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Paperback. Condition: new. Paperback. 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 structureUse the Cassandra Query Language (CQL) and cqlsh (the CQL shell)Create a working data model and compare it with an equivalent relational modelDesign and develop applications using client driversExplore cluster topology and learn how nodes exchange dataMaintain a high level of performance in your clusterDeploy Cassandra onsite, in the cloud, or with Docker and KubernetesIntegrate Cassandra with Spark, Kafka, Elasticsearch, Solr, and Lucene 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781492097143
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Paperback. Condition: New. 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 structureUse the Cassandra Query Language (CQL) and cqlsh (the CQL shell)Create a working data model and compare it with an equivalent relational modelDesign and develop applications using client driversExplore cluster topology and learn how nodes exchange dataMaintain a high level of performance in your clusterDeploy Cassandra onsite, in the cloud, or with Docker and KubernetesIntegrate Cassandra with Spark, Kafka, Elasticsearch, Solr, and Lucene. Seller Inventory # LU-9781492097143
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