Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems. Martin Kleppmann

Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems


Designing.Data.Intensive.Applications.The.Big.Ideas.Behind.Reliable.Scalable.and.Maintainable.Systems.pdf
ISBN: 9781449373320 | 500 pages | 13 Mb


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Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems Martin Kleppmann
Publisher: O'Reilly Media, Incorporated



Everybody has an intuitive idea of what it means for software to be reliable or unreliable. Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems. Pentaho Hadoop for the Enterprise: Making Data Management Massively Scalable, Agile, Feature-Rich, and Cost-Effective Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems. Fishpond Australia, Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems. A data-intensive application is typically built from standard building are trying to achieve: reliabile, scalabile and maintainable data systems. Implementation detail behind a clean, simple-to-understand façade. Big Data: Principles and best practices of scalable realtime data systems. Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems · Martin Kleppmann Paperback. Filename, : Joinebook.com_OReilly.Media.Designing.Data.Intensive.Applications .April.2015.pdf. Product: Business Analytics, Data Integration, Big Data Analytics, Embedded Analytics. Big Data for Chimps: A Guide to Massive-Scale Data Processing in Practice. Scores of database management systems across the Internet access and maintain large amounts of structured data for Back. Philip (flip) Kromer Paperback.





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