Scalable Data Management For Future Hardware

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Scalable Data Management For Future Hardware

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Author : Kai-Uwe Sattler
language : en
Publisher: Springer Nature
Release Date : 2025-01-23

Scalable Data Management For Future Hardware written by Kai-Uwe Sattler and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-23 with Computers categories.

This open access book presents the results of the DFG priority program on Scalable Data Management for Future Hardware. It details requirements and solutions of how modern and future hardware architectures can be leveraged to address the challenges in modern data management. The nine chapters of the book present a wide range of data management architectures in conjunction with current hardware developments, often related to applications in data analytics or machine learning. They cover topics such as hardware-accelerated query or event processing on FPGA, GPU, and multicore CPUs, scalable data management in data center networks or on modern memory and storage technologies, and operating system support. This book provides researchers in academia and industry with a comprehensive combination of data management, operating systems, distributed systems and computer architecture issues necessary to address the requirements from practice as well as to propel innovative ideas and challenging research questions.

Architecture Of Computing Systems Arcs 2020

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Author : André Brinkmann
language : en
Publisher: Springer Nature
Release Date : 2020-07-09

Architecture Of Computing Systems Arcs 2020 written by André Brinkmann and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-09 with Computers categories.

This book constitutes the proceedings of the 33rd International Conference on Architecture of Computing Systems, ARCS 2020, held in Aachen, Germany, in May 2020.* The 12 full papers in this volume were carefully reviewed and selected from 33 submissions. 6 workshop papers are also included. ARCS has always been a conference attracting leading-edge research outcomes in Computer Architecture and Operating Systems, including a wide spectrum of topics ranging from embedded and real-time systems all the way to large-scale and parallel systems. The selected papers focus on concepts and tools for incorporating self-adaptation and self-organization mechanisms in high-performance computing systems. This includes upcoming approaches for runtime modifications at various abstraction levels, ranging from hardware changes to goal changes and their impact on architectures, technologies, and languages. *The conference was canceled due to the COVID-19 pandemic.

Advances In Databases And Information Systems

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Author : Alberto Abelló
language : en
Publisher: Springer Nature
Release Date : 2023-08-27

Advances In Databases And Information Systems written by Alberto Abelló and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-27 with Computers categories.

This book constitutes the proceedings of the 27th European Conference on Advances in Databases and Information Systems, ADBIS 2023, held in Barcelona, Spain, during September 4–7, 2023. The 11 full papers presented in this book together with 3 keynotes and tutorials were carefully reviewed and selected from 77 submissions. The papers are organized in the following topical sections: keynote talk and tutorials; query processing and data exploration, data science and fairness and Data and Metadata Quality

Architecting The Future Of Data Oracle Sharding Cloud Intelligence And Scalable Enterprise Systems 2025

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Author : Author:1- Sarvesh Kumar Gupta, Author:2-Dr. Lalit Kumar
language : en
Publisher: RAVEENA PRAKASHAN OPC PVT LTD
Release Date :

Architecting The Future Of Data Oracle Sharding Cloud Intelligence And Scalable Enterprise Systems 2025 written by Author:1- Sarvesh Kumar Gupta, Author:2-Dr. Lalit Kumar and has been published by RAVEENA PRAKASHAN OPC PVT LTD this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.

PREFACE In the digital age, data has become the driving force behind business decision-making, customer experiences, and technological innovation. As organizations strive to harness the full potential of their data, the need for scalable, efficient, and resilient data architectures has never been greater. Traditional monolithic database systems are often insufficient to handle the massive volumes, variety, and velocity of data generated by modern enterprises. Enter Oracle Sharding, Cloud Intelligence, and scalable enterprise systems—the cornerstone technologies that enable organizations to meet the demands of the data-driven future.Architecting the Future of Data: Oracle Sharding, Cloud Intelligence, and Scalable Enterprise Systems offers a comprehensive exploration of how these cutting-edge technologies are reshaping the landscape of enterprise data management. This book provides in-depth insights into how organizations can design and implement scalable, cloud-native database architectures that allow for seamless data distribution, faster processing, and enhanced performance. By focusing on Oracle Sharding, cloud intelligence, and enterprise scalability, this book aims to equip IT professionals, data architects, and business leaders with the knowledge and tools required to build the next generation of enterprise systems. The foundation of this book is Oracle’s Sharding technology, which offers an innovative approach to database architecture by horizontally partitioning data across multiple databases, or shards. This approach enhances both performance and scalability, allowing organizations to process vast amounts of data across distributed environments while ensuring high availability, fault tolerance, and efficient resource utilization. As businesses increasingly adopt cloud platforms, Oracle Sharding proves to be a critical tool for managing data in distributed cloud environments, ensuring seamless data access and faster query performance even as data volumes grow exponentially. Furthermore, cloud intelligence plays a pivotal role in enabling organizations to build smarter, more adaptive systems. As cloud technologies evolve, leveraging intelligent data processing, machine learning (ML), and artificial intelligence (AI) has become a game-changer for businesses looking to extract deeper insights from their data and improve operational efficiencies. This book delves into how cloud intelligence, when integrated with scalable data architectures like Oracle Sharding, allows enterprises to process, analyze, and gain real-time insights from massive datasets. The ability to deploy AI models directly within the cloud infrastructure enhances predictive capabilities, automates decision-making processes, and drives innovation. Scalable enterprise systems are essential for organizations to maintain their competitive edge in a rapidly changing business environment. As companies expand their digital footprints and create more data-intensive applications, the need for scalable, distributed data architectures has become crucial. This book explores the design principles and best practices for creating cloud-native enterprise systems that can adapt to growing data demands while ensuring high performance and security. By understanding the synergy between Oracle Sharding and cloud intelligence, organizations can build resilient systems capable of handling the complexities of modern data workflows. Throughout the chapters, we will cover not only the technical aspects of these technologies but also real-world use cases and best practices from leading companies who have successfully adopted Oracle Sharding and cloud-based data architectures. This book aims to bridge the gap between theoretical concepts and practical implementation, offering readers actionable strategies for building scalable, cloud-native data systems that align with business goals and technological advancements. As organizations continue to embrace digital transformation and the cloud becomes the backbone of modern IT infrastructure, understanding how to design and implement scalable, intelligent data architectures is more critical than ever. Whether you are an IT architect, database administrator, or business leader, Architecting the Future of Data will provide you with the insights and strategies necessary to navigate the challenges and opportunities of modern data management. The future of data is distributed, intelligent, and scalable—this book will guide you in shaping that future within your organization. Authors

Designing Data Intensive Applications

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Author : Martin Kleppmann
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-03-16

Designing Data Intensive Applications written by Martin Kleppmann 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 2017-03-16 with Computers categories.

Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

Data Management In The Cloud

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Author : Divyakant Agrawal
language : en
Publisher: Springer Nature
Release Date : 2022-05-31

Data Management In The Cloud written by Divyakant Agrawal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.

Cloud computing has emerged as a successful paradigm of service-oriented computing and has revolutionized the way computing infrastructure is used. This success has seen a proliferation in the number of applications that are being deployed in various cloud platforms. There has also been an increase in the scale of the data generated as well as consumed by such applications. Scalable database management systems form a critical part of the cloud infrastructure. The attempt to address the challenges posed by the management of big data has led to a plethora of systems. This book aims to clarify some of the important concepts in the design space of scalable data management in cloud computing infrastructures. Some of the questions that this book aims to answer are: the appropriate systems for a specific set of application requirements, the research challenges in data management for the cloud, and what is novel in the cloud for database researchers? We also aim to address one basic question: whether cloud computing poses new challenges in scalable data management or it is just a reincarnation of old problems? We provide a comprehensive background study of state-of-the-art systems for scalable data management and analysis. We also identify important aspects in the design of different systems and the applicability and scope of these systems. A thorough understanding of current solutions and a precise characterization of the design space are essential for clearing the "cloudy skies of data management" and ensuring the success of DBMSs in the cloud, thus emulating the success enjoyed by relational databases in traditional enterprise settings. Table of Contents: Introduction / Distributed Data Management / Cloud Data Management: Early Trends / Transactions on Co-located Data / Transactions on Distributed Data / Multi-tenant Database Systems / Concluding Remarks

Infoworld

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Author :
language : en
Publisher:
Release Date : 1993-11-29

Infoworld written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-11-29 with categories.

InfoWorld is targeted to Senior IT professionals. Content is segmented into Channels and Topic Centers. InfoWorld also celebrates people, companies, and projects.

Modin For Scalable Data Science

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Author : William Smith
language : en
Publisher: HiTeX Press
Release Date : 2025-07-24

Modin For Scalable Data Science written by William Smith and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-24 with Computers categories.

"Modin for Scalable Data Science" In the era of massive datasets and ever-expanding analytics pipelines, "Modin for Scalable Data Science" is a comprehensive guide for data engineers and scientists determined to break through the limits of single-node data workflows. The book opens by analyzing the bottlenecks inherent in contemporary data science, from memory and CPU constraints in pandas to the challenges of distributed data movement. It offers a thorough survey of modern distributed frameworks such as Spark and Dask, before introducing Modin—a breakthrough library that bridges the ease of pandas with the power of distributed computing. Real-world use cases, including large-scale ETL, feature engineering, and interactive analytics, highlight the practical motivations behind adopting scalable data science solutions. Diving deep into Modin’s architecture, the book explores its pluggable execution backends, innovative task graph design, and robust integration with crucial data science and machine learning ecosystems like NumPy, scikit-learn, and RAPIDS. Readers learn best practices for deploying and tuning Modin in diverse environments: from laptops to cloud clusters, containerized solutions via Kubernetes, and advanced resource management in production-grade settings. Thorough attention is paid to security, data locality, and the nuances of environment-specific configuration, ensuring readers gain both strategic understanding and actionable know-how for leveraging Modin at scale. As a hands-on reference, the book meticulously details Modin’s compatibility with pandas, approaches to debugging distributed DataFrames, and advanced profiling and optimization techniques. It empowers practitioners to automate machine learning pipelines, handle real-time inference, and scale MLOps with tools such as Ray Tune and Kubeflow. For those looking to extend or contribute to Modin, the closing chapters provide blueprints for plugin development, internal API mastery, and effective engagement with the open source community. This guide is essential for anyone seeking to harness the full potential of distributed data science without sacrificing the simplicity of familiar Python workflows.

Apache Sedona Essentials

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Author : Robert Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-01-06

Apache Sedona Essentials written by Robert 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 2025-01-06 with Computers categories.

"Apache Sedona Essentials: A Practical Guide to Spatial Data Processing" is meticulously crafted for beginners and professionals alike, offering a comprehensive overview of Apache Sedona's capabilities and applications in handling spatial data. This book serves as a definitive resource, equipping readers with the foundation needed to manage, query, and analyze spatial datasets efficiently using Sedona. Each chapter is structured to guide you progressively through core concepts and advanced techniques, ensuring a robust understanding of the functionalities that Apache Sedona provides. Focused on real-world applicability, this guide explores Sedona's integration within big data ecosystems, its performance optimization strategies, and the implementation of advanced spatial processing methods. From setting up your development environment to exploring complex spatial operations and deriving insights from data analytics, this book prepares you to tackle a variety of spatial data challenges across diverse domains. Through practical examples, detailed explanations, and best practice recommendations, readers will gain the skills needed to harness the full potential of spatial data intelligence using Apache Sedona.

Scalable Artificial Intelligence For Healthcare

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Author : Houneida Sakly
language : en
Publisher: CRC Press
Release Date : 2025-05-06

Scalable Artificial Intelligence For Healthcare written by Houneida Sakly and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-06 with Computers categories.

This edited volume examines the transformative impact of AI technologies on global healthcare systems, with a focus on enhancing efficiency and accessibility. The content provides a comprehensive exploration of the principles and practices required to scale AI applications in healthcare, addressing areas such as diagnosis, treatment, and patient care. Key topics include data scalability, model deployment, and infrastructure design, highlighting the use of microservices, containerization, cloud computing, and big data technologies in building scalable AI systems. Discussions cover advancements in machine learning models, distributed processing, and transfer learning, alongside critical considerations such as continuous integration, data privacy, and ethics. Real-world case studies depict both the successes and challenges of implementing scalable AI across various healthcare environments, offering valuable insights for future advancements. This volume serves as a practical and theoretical guide for healthcare professionals, AI researchers, and technology enthusiasts seeking to develop or expand on AI-driven healthcare solutions to address global health challenges effectively.