In Memory Database Management Systems
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| Author | : Joy Arulraj |
| Publisher | : Springer Nature |
| Total Pages | : 173 |
| Release | : 2022-06-01 |
| Genre | : Computers |
| ISBN | : 3031018680 |
This book explores the implications of non-volatile memory (NVM) for database management systems (DBMSs). The advent of NVM will fundamentally change the dichotomy between volatile memory and durable storage in DBMSs. These new NVM devices are almost as fast as volatile memory, but all writes to them are persistent even after power loss. Existing DBMSs are unable to take full advantage of this technology because their internal architectures are predicated on the assumption that memory is volatile. With NVM, many of the components of legacy DBMSs are unnecessary and will degrade the performance of data-intensive applications. We present the design and implementation of DBMS architectures that are explicitly tailored for NVM. The book focuses on three aspects of a DBMS: (1) logging and recovery, (2) storage and buffer management, and (3) indexing. First, we present a logging and recovery protocol that enables the DBMS to support near-instantaneous recovery. Second, we propose a storage engine architecture and buffer management policy that leverages the durability and byte-addressability properties of NVM to reduce data duplication and data migration. Third, the book presents the design of a range index tailored for NVM that is latch-free yet simple to implement. All together, the work described in this book illustrates that rethinking the fundamental algorithms and data structures employed in a DBMS for NVM improves performance and availability, reduces operational cost, and simplifies software development.
| Author | : Hasso Plattner |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 286 |
| Release | : 2012-04-17 |
| Genre | : Business & Economics |
| ISBN | : 3642295754 |
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.
| Author | : Frans Faerber |
| Publisher | : Foundations and Trends in Databases |
| Total Pages | : 144 |
| Release | : 2017-07-20 |
| Genre | : Probabilistic databases |
| ISBN | : 9781680833249 |
With growing memory sizes and memory prices dropping by a factor of 10 every 5 years, data having a "primary home" in memory is now a reality. Main-memory databases eschew many of the traditional architectural pillars of relational database systems that optimized for disk-resident data. The result of these memory-optimized designs are systems that feature several innovative approaches to fundamental issues (e.g., concurrency control, query processing) that achieve orders of magnitude performance improvements over traditional designs. This monograph provides an overview of recent developments in main-memory database systems. It covers five main issues and architectural choices that need to be made when building a high performance main-memory optimized database: data organization and storage, indexing, concurrency control, durability and recovery techniques, and query processing and compilation. The monograph focuses on four commercial and research systems: H-Store/VoltDB, Hekaton, HyPer, and SAPHANA. These systems are diverse in their design choices and form a representative sample of the state of the art in main-memory database systems. It also covers other commercial and academic systems, along with current and future research trends.
| Author | : Hasso Plattner |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 245 |
| Release | : 2011-03-08 |
| Genre | : Business & Economics |
| ISBN | : 3642193633 |
In the last 50 years the world has been completely transformed through the use of IT. We have now reached a new inflection point. Here we present, for the first time, how in-memory computing is changing the way businesses are run. Today, enterprise data is split into separate databases for performance reasons. Analytical data resides in warehouses, synchronized periodically with transactional systems. This separation makes flexible, real-time reporting on current data impossible. 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. We describe techniques that allow analytical and transactional processing at the speed of thought and enable new ways of doing business. The book is intended for university students, IT-professionals and IT-managers, but also for senior management who wish to create new business processes by leveraging in-memory computing.
| Author | : Alex Petrov |
| Publisher | : O'Reilly Media |
| Total Pages | : 373 |
| Release | : 2019-09-13 |
| Genre | : Computers |
| ISBN | : 1492040312 |
When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it’s often difficult to understand what each one offers and how they differ. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals. Throughout the book, you’ll explore relevant material gleaned from numerous books, papers, blog posts, and the source code of several open source databases. These resources are listed at the end of parts one and two. You’ll discover that the most significant distinctions among many modern databases reside in subsystems that determine how storage is organized and how data is distributed. This book examines: Storage engines: Explore storage classification and taxonomy, and dive into B-Tree-based and immutable Log Structured storage engines, with differences and use-cases for each Storage building blocks: Learn how database files are organized to build efficient storage, using auxiliary data structures such as Page Cache, Buffer Pool and Write-Ahead Log Distributed systems: Learn step-by-step how nodes and processes connect and build complex communication patterns Database clusters: Which consistency models are commonly used by modern databases and how distributed storage systems achieve consistency
| Author | : Nabil R. Adam |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 476 |
| Release | : 1993-12-08 |
| Genre | : Computers |
| ISBN | : 9783540575078 |
Database management is attracting wide interest in both academic and industrial contexts. New application areas such as CAD/CAM, geographic information systems, and multimedia are emerging. The needs of these application areas are far more complex than those of conventional business applications. The purpose of this book is to bring together a set of current research issues that addresses a broad spectrum of topics related to database systems and applications. The book is divided into four parts: - object-oriented databases, - temporal/historical database systems, - query processing in database systems, - heterogeneity, interoperability, open system architectures, multimedia database systems.
| Author | : Christian Tinnefeld |
| Publisher | : Springer |
| Total Pages | : 139 |
| Release | : 2015-07-07 |
| Genre | : Computers |
| ISBN | : 3319207113 |
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.
| Author | : Joseph M. Hellerstein |
| Publisher | : MIT Press |
| Total Pages | : 884 |
| Release | : 2005 |
| Genre | : Computers |
| ISBN | : 9780262693141 |
The latest edition of a popular text and reference on database research, with substantial new material and revision; covers classical literature and recent hot topics. Lessons from database research have been applied in academic fields ranging from bioinformatics to next-generation Internet architecture and in industrial uses including Web-based e-commerce and search engines. The core ideas in the field have become increasingly influential. This text provides both students and professionals with a grounding in database research and a technical context for understanding recent innovations in the field. The readings included treat the most important issues in the database area--the basic material for any DBMS professional. This fourth edition has been substantially updated and revised, with 21 of the 48 papers new to the edition, four of them published for the first time. Many of the sections have been newly organized, and each section includes a new or substantially revised introduction that discusses the context, motivation, and controversies in a particular area, placing it in the broader perspective of database research. Two introductory articles, never before published, provide an organized, current introduction to basic knowledge of the field; one discusses the history of data models and query languages and the other offers an architectural overview of a database system. The remaining articles range from the classical literature on database research to treatments of current hot topics, including a paper on search engine architecture and a paper on application servers, both written expressly for this edition. The result is a collection of papers that are seminal and also accessible to a reader who has a basic familiarity with database systems.
| Author | : Pedro Mejia Alvarez |
| Publisher | : Springer Nature |
| Total Pages | : 115 |
| Release | : 2022-09-13 |
| Genre | : Computers |
| ISBN | : 3031132955 |
This book provides basic knowledge about main memory management in relational databases as it is needed to support large-scale applications processed completely in memory. In business operations, real-time predictability and high speed is a must. Hence every opportunity must be exploited to improve performance, including reducing dependency on the hard disk, adding more memory to make more data resident in the memory, and even deploying an in-memory system where all data can be kept in memory. The book provides one chapter for each of the main related topics, i.e. the memory system, memory management, virtual memory, and databases and their memory systems, and it is complemented by a short survey of six commercial systems: TimesTen, MySQL, VoltDB, Hekaton, HyPer/ScyPer, and SAP HANA.
| Author | : W.H. Inmon |
| Publisher | : Academic Press |
| Total Pages | : 434 |
| Release | : 2019-04-30 |
| Genre | : Computers |
| ISBN | : 0128169176 |
Over the past 5 years, the concept of big data has matured, data science has grown exponentially, and data architecture has become a standard part of organizational decision-making. Throughout all this change, the basic principles that shape the architecture of data have remained the same. There remains a need for people to take a look at the "bigger picture" and to understand where their data fit into the grand scheme of things. Data Architecture: A Primer for the Data Scientist, Second Edition addresses the larger architectural picture of how big data fits within the existing information infrastructure or data warehousing systems. This is an essential topic not only for data scientists, analysts, and managers but also for researchers and engineers who increasingly need to deal with large and complex sets of data. Until data are gathered and can be placed into an existing framework or architecture, they cannot be used to their full potential. Drawing upon years of practical experience and using numerous examples and case studies from across various industries, the authors seek to explain this larger picture into which big data fits, giving data scientists the necessary context for how pieces of the puzzle should fit together. - New case studies include expanded coverage of textual management and analytics - New chapters on visualization and big data - Discussion of new visualizations of the end-state architecture
