In Memory Data Management And Analysis
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In Memory Data Management And Analysis
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Author : Arun Jagatheesan
language : en
Publisher: Springer
Release Date : 2015-01-13
In Memory Data Management And Analysis written by Arun Jagatheesan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-13 with Computers categories.
This book constitutes the thoroughly refereed post conference proceedings of the First and Second International Workshops on In Memory Data Management and Analysis held in Riva del Garda, Italy, August 2013 and Hangzhou, China, in September 2014. The 11 revised full papers were carefully reviewed and selected from 18 submissions and cover topics from main-memory graph analytics platforms to main-memory OLTP applications.
In Memory Data Management
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Author : Hasso Plattner
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-05-14
In Memory Data Management written by Hasso Plattner and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-14 with Business & Economics categories.
This book examines for the first time, the ways that in-memory computing is changing the way businesses are run. The authors describe techniques that allow analytical and transactional processing at the speed of thought and enable new ways of doing business.
In Memory Data Management
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Author : Hasso Plattner
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-04-17
In Memory Data Management written by Hasso Plattner and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-04-17 with Business & Economics categories.
In the last fifty years the world has been completely transformed through the use of IT. We have now reached a new inflection point. This book presents, for the first time, how in-memory data management is changing the way businesses are run. Today, enterprise data is split into separate databases for performance reasons. Multi-core CPUs, large main memories, cloud computing and powerful mobile devices are serving as the foundation for the transition of enterprises away from this restrictive model. This book provides the technical foundation for processing combined transactional and analytical operations in the same database. In the year since we published the first edition of this book, the performance gains enabled by the use of in-memory technology in enterprise applications has truly marked an inflection point in the market. The new content in this second edition focuses on the development of these in-memory enterprise applications, showing how they leverage the capabilities of in-memory technology. The book is intended for university students, IT-professionals and IT-managers, but also for senior management who wish to create new business processes.
The In Memory Revolution
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Author : Hasso Plattner
language : en
Publisher: Springer
Release Date : 2015-12-28
The In Memory Revolution written by Hasso Plattner and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-28 with Business & Economics categories.
This book describes the next generation of business applications in the innovative new SAP Business Suite 4 SAP HANA (SAP S/4HANA), exploiting the revolutionary capabilities of the SAP HANA in-memory database. Numerous real-world examples are presented illustrating the disruptive potential of this technology and the quantum leap it has facilitated in terms of simplicity, flexibility, and speed for new applications. The intuitive structure of this book offers a straightforward business perspective grounded in technology in order to enable valuable business insights drawn from the wealth of real-world experience of the book’s two authors, both prominent figures in the field of business application systems: Hasso Plattner and Bernd Leukert. Hasso Plattner is the co-founder of SAP and the founder of the Hasso Plattner Institute, affiliated with the University of Potsdam, Germany. Bernd Leukert is a member of the SAP Executive Board and the Global Managing Board of SAP.
Big Data Management And Processing
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Author : Kuan-Ching Li
language : en
Publisher: CRC Press
Release Date : 2017-05-19
Big Data Management And Processing written by Kuan-Ching Li and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-19 with Business & Economics categories.
From the Foreword: "Big Data Management and Processing is [a] state-of-the-art book that deals with a wide range of topical themes in the field of Big Data. The book, which probes many issues related to this exciting and rapidly growing field, covers processing, management, analytics, and applications... [It] is a very valuable addition to the literature. It will serve as a source of up-to-date research in this continuously developing area. The book also provides an opportunity for researchers to explore the use of advanced computing technologies and their impact on enhancing our capabilities to conduct more sophisticated studies." ---Sartaj Sahni, University of Florida, USA "Big Data Management and Processing covers the latest Big Data research results in processing, analytics, management and applications. Both fundamental insights and representative applications are provided. This book is a timely and valuable resource for students, researchers and seasoned practitioners in Big Data fields. --Hai Jin, Huazhong University of Science and Technology, China Big Data Management and Processing explores a range of big data related issues and their impact on the design of new computing systems. The twenty-one chapters were carefully selected and feature contributions from several outstanding researchers. The book endeavors to strike a balance between theoretical and practical coverage of innovative problem solving techniques for a range of platforms. It serves as a repository of paradigms, technologies, and applications that target different facets of big data computing systems. The first part of the book explores energy and resource management issues, as well as legal compliance and quality management for Big Data. It covers In-Memory computing and In-Memory data grids, as well as co-scheduling for high performance computing applications. The second part of the book includes comprehensive coverage of Hadoop and Spark, along with security, privacy, and trust challenges and solutions. The latter part of the book covers mining and clustering in Big Data, and includes applications in genomics, hospital big data processing, and vehicular cloud computing. The book also analyzes funding for Big Data projects.
A Course In In Memory Data Management
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Author : Hasso Plattner
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-22
A Course In In Memory Data Management written by Hasso Plattner and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-22 with Business & Economics categories.
Recent achievements in hardware and software development, such as multi-core CPUs and DRAM capacities of multiple terabytes per server, enabled the introduction of a revolutionary technology: in-memory data management. This technology supports the flexible and extremely fast analysis of massive amounts of enterprise data. Professor Hasso Plattner and his research group at the Hasso Plattner Institute in Potsdam, Germany, have been investigating and teaching the corresponding concepts and their adoption in the software industry for years. This book is based on the first online course on the openHPI e-learning platform, which was launched in autumn 2012 with more than 13,000 learners. The book is designed for students of computer science, software engineering, and IT related subjects. However, it addresses business experts, decision makers, software developers, technology experts, and IT analysts alike. Plattner and his group focus on exploring the inner mechanics of a column-oriented dictionary-encoded in-memory database. Covered topics include - amongst others - physical data storage and access, basic database operators, compression mechanisms, and parallel join algorithms. Beyond that, implications for future enterprise applications and their development are discussed. Readers are lead to understand the radical differences and advantages of the new technology over traditional row-oriented disk-based databases.
Building A Columnar Database On Ramcloud
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Author : Christian Tinnefeld
language : en
Publisher: Springer
Release Date : 2015-07-07
Building A Columnar Database On Ramcloud written by Christian Tinnefeld and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-07 with Computers categories.
This book examines the field of parallel database management systems and illustrates the great variety of solutions based on a shared-storage or a shared-nothing architecture. Constantly dropping memory prices and the desire to operate with low-latency responses on large sets of data paved the way for main memory-based parallel database management systems. However, this area is currently dominated by the shared-nothing approach in order to preserve the in-memory performance advantage by processing data locally on each server. The main argument this book makes is that such an unilateral development will cease due to the combination of the following three trends: a) Today’s network technology features remote direct memory access (RDMA) and narrows the performance gap between accessing main memory on a server and of a remote server to and even below a single order of magnitude. b) Modern storage systems scale gracefully, are elastic and provide high-availability. c) A modern storage system such as Stanford’s RAM Cloud even keeps all data resident in the main memory. Exploiting these characteristics in the context of a main memory-based parallel database management system is desirable. The book demonstrates that the advent of RDMA-enabled network technology makes the creation of a parallel main memory DBMS based on a shared-storage approach feasible.
Data Analytics With Hadoop
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Author : Benjamin Bengfort
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-06
Data Analytics With Hadoop written by Benjamin Bengfort and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06 with Computers categories.
Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you’ll focus on particular analyses you can build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce. Data scientists and analysts will learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling and data management with Spark MLlib, Hive, and HBase. You’ll also learn about the analytical processes and data systems available to build and empower data products that can handle—and actually require—huge amounts of data. Understand core concepts behind Hadoop and cluster computing Use design patterns and parallel analytical algorithms to create distributed data analysis jobs Learn about data management, mining, and warehousing in a distributed context using Apache Hive and HBase Use Sqoop and Apache Flume to ingest data from relational databases Program complex Hadoop and Spark applications with Apache Pig and Spark DataFrames Perform machine learning techniques such as classification, clustering, and collaborative filtering with Spark’s MLlib
Aws Timestream Data Management And Analysis
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Author : Richard Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-05-28
Aws Timestream Data Management And Analysis written by Richard Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-28 with Computers categories.
"AWS Timestream Data Management and Analysis" Discover the definitive guide to harnessing the power of AWS Timestream with "AWS Timestream Data Management and Analysis." Designed for architects, engineers, and analytic professionals, this comprehensive book delves deeply into time series data concepts and the unique architectural foundations underpinning Timestream. It offers a clear exploration of how AWS Timestream compares to traditional RDBMS, NoSQL, and other time series solutions, highlighting its data structures, scalability strategies, and ideal deployment scenarios in the modern cloud. The book provides hands-on guidance for provisioning, configuring, and optimizing Timestream environments at every stage of the data lifecycle. Readers will gain practical insights into efficient data ingestion—batch, micro-batch, and streaming—as well as robust integration with AWS services like Kinesis, Lambda, QuickSight, and Glue. Detailed chapters address advanced data modeling, analytics, and storage optimization techniques, along with cost management, security best practices, compliance frameworks, and performance tuning. Each topic is presented through clear explanations and actionable patterns, empowering professionals to architect reliable, high-performance time series solutions for IoT, DevOps, financial, and manufacturing applications. Looking toward the future, the book explores emerging innovations such as serverless analytics, edge computing, AI/ML integrations, and zero-ETL architectures, while also surveying open standards and next-generation cloud strategies. Real-world case studies and industry applications illustrate Timestream’s value across diverse sectors, providing readers with practical blueprints for success. Whether you're building scalable telemetry pipelines, predictive analytics engines, or secure, multi-tenant data architectures, this authoritative guide offers the tools, context, and confidence to excel with AWS Timestream.
Design Patterns For Cloud Native Applications
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Author : Kasun Indrasiri
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-05-17
Design Patterns For Cloud Native Applications written by Kasun Indrasiri and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-17 with Computers categories.
With the immense cost savings and scalability the cloud provides, the rationale for building cloud native applications is no longer in question. The real issue is how. With this practical guide, developers will learn about the most commonly used design patterns for building cloud native applications using APIs, data, events, and streams in both greenfield and brownfield development. You'll learn how to incrementally design, develop, and deploy large and effective cloud native applications that you can manage and maintain at scale with minimal cost, time, and effort. Authors Kasun Indrasiri and Sriskandarajah Suhothayan highlight use cases that effectively demonstrate the challenges you might encounter at each step. Learn the fundamentals of cloud native applications Explore key cloud native communication, connectivity, and composition patterns Learn decentralized data management techniques Use event-driven architecture to build distributed and scalable cloud native applications Explore the most commonly used patterns for API management and consumption Examine some of the tools and technologies you'll need for building cloud native systems