Download or read book Data Access for Highly Scalable Solutions written by Douglas McMurtry and published by Microsoft patterns & practices. This book was released on 2013-09-30 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: All applications use data, and most applications also need to store this data somewhere. In the world of business solutions, this often meant creating a relational database. However, relational technology is not always the best solution to meet the increasingly complex data-processing requirements of modern business systems, especially when this processing involves storing and retrieving massive amounts of data. The advent of NoSQL databases has changed the way in which organizations have started to think about the way in which they structure their data. There is no standard definition of what a NoSQL database is other than they are all non-relational. They are less generalized than relational databases, but the driving force behind most NoSQL databases is focused efficiency and high scalability. The downside of NoSQL is that no single database is likely to be able to support the complete range of business requirements mandated by your applications. How do you select the most appropriate database to use, or should you remain with the relational model? A modern business application is not restricted to using a single data store, and an increasing number of solutions are now based on a polyglot architecture. The key to designing a successful application is to understand which databases best meet the needs of the various parts of the system, and how to combine these databases into a single, seamless solution. This guide helps you understand these challenges and enables you to apply the principles of NoSQL databases and polyglot solutions in your own environment. To help illustrate how to build a polyglot solution, this guide presents a case study of a fictitious company faced with building a highly scalable web application capable of supporting many thousands of concurrent users.

Download or read book Building Highly Scalable Database Applications with NET written by Wallace B. McClure and published by John Wiley & Sons. This book was released on 2002-06-25 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the only book on the market to focus on addressing issues of building highly scalable database applications with .NET technologies. Comprehensive coverage includes building .NET applications for all the major RDBMSs: SQL Server, Oracle, DB2, and MySQL.

Download or read book Big Data written by James Warren and published by Simon and Schuster. This book was released on 2015-04-29 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive. Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases. This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. What's Inside Introduction to big data systems Real-time processing of web-scale data Tools like Hadoop, Cassandra, and Storm Extensions to traditional database skills About the Authors Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing. Table of Contents A new paradigm for Big Data PART 1 BATCH LAYER Data model for Big Data Data model for Big Data: Illustration Data storage on the batch layer Data storage on the batch layer: Illustration Batch layer Batch layer: Illustration An example batch layer: Architecture and algorithms An example batch layer: Implementation PART 2 SERVING LAYER Serving layer Serving layer: Illustration PART 3 SPEED LAYER Realtime views Realtime views: Illustration Queuing and stream processing Queuing and stream processing: Illustration Micro-batch stream processing Micro-batch stream processing: Illustration Lambda Architecture in depth

Download or read book Scalable Big Data Architecture written by Bahaaldine Azarmi and published by Apress. This book was released on 2015-12-31 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the different types of data architecture and illustrates the many possibilities hidden behind the term "Big Data", from the usage of No-SQL databases to the deployment of stream analytics architecture, machine learning, and governance. Scalable Big Data Architecture covers real-world, concrete industry use cases that leverage complex distributed applications , which involve web applications, RESTful API, and high throughput of large amount of data stored in highly scalable No-SQL data stores such as Couchbase and Elasticsearch. This book demonstrates how data processing can be done at scale from the usage of NoSQL datastores to the combination of Big Data distribution. When the data processing is too complex and involves different processing topology like long running jobs, stream processing, multiple data sources correlation, and machine learning, it’s often necessary to delegate the load to Hadoop or Spark and use the No-SQL to serve processed data in real time. This book shows you how to choose a relevant combination of big data technologies available within the Hadoop ecosystem. It focuses on processing long jobs, architecture, stream data patterns, log analysis, and real time analytics. Every pattern is illustrated with practical examples, which use the different open sourceprojects such as Logstash, Spark, Kafka, and so on. Traditional data infrastructures are built for digesting and rendering data synthesis and analytics from large amount of data. This book helps you to understand why you should consider using machine learning algorithms early on in the project, before being overwhelmed by constraints imposed by dealing with the high throughput of Big data. Scalable Big Data Architecture is for developers, data architects, and data scientists looking for a better understanding of how to choose the most relevant pattern for a Big Data project and which tools to integrate into that pattern.

Download or read book The Defintive Guide to Building Highly Scalable Enterprise File Serving Solutions written by Realtimepublishers.com and published by Realtimepublishers.com. This book was released on 2005 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Designing Data Intensive Applications written by Martin Kleppmann and published by "O'Reilly Media, Inc.". This book was released on 2017-03-16 with total page 658 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Foundations of Scalable Systems written by Ian Gorton and published by "O'Reilly Media, Inc.". This book was released on 2022-06-30 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: In many systems, scalability becomes the primary driver as the user base grows. Attractive features and high utility breed success, which brings more requests to handle and more data to manage. But organizations reach a tipping point when design decisions that made sense under light loads suddenly become technical debt. This practical book covers design approaches and technologies that make it possible to scale an application quickly and cost-effectively. Author Ian Gorton takes software architects and developers through the foundational principles of distributed systems. You'll explore the essential ingredients of scalable solutions, including replication, state management, load balancing, and caching. Specific chapters focus on the implications of scalability for databases, microservices, and event-based streaming systems. You will focus on: Foundations of scalable systems: Learn basic design principles of scalability, its costs, and architectural tradeoffs Designing scalable services: Dive into service design, caching, asynchronous messaging, serverless processing, and microservices Designing scalable data systems: Learn data system fundamentals, NoSQL databases, and eventual consistency versus strong consistency Designing scalable streaming systems: Explore stream processing systems and scalable event-driven processing

Download or read book Building Scalable and High performance Java Web Applications Using J2EE Technology written by Greg Barish and published by Addison-Wesley Professional. This book was released on 2002 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scaling Java enterprise applications beyond just programming techniques--this is the next level. This volume covers all the technologies Java developers need to build scalable, high-performance Web applications. The book also covers servlet-based session management, EJB application logic, database design and integration, and more.

Download or read book The Art of Scalability written by Martin L. Abbott and published by Pearson Education. This book was released on 2009-12-15 with total page 1063 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Comprehensive, Proven Approach to IT Scalability from Two Veteran Software, Technology, and Business Executives In The Art of Scalability, AKF Partners cofounders Martin L. Abbott and Michael T. Fisher cover everything IT and business leaders must know to build technology infrastructures that can scale smoothly to meet any business requirement. Drawing on their unparalleled experience managing some of the world’s highest-transaction-volume Web sites, the authors provide detailed models and best-practice approaches available in no other book. Unlike previous books on scalability, The Art of Scalability doesn’t limit its coverage to technology. Writing for both technical and nontechnical decision-makers, this book covers everything that impacts scalability, including architecture, processes, people, and organizations. Throughout, the authors address a broad spectrum of real-world challenges, from performance testing to IT governance. Using their tools and guidance, organizations can systematically overcome obstacles to scalability and achieve unprecedented levels of technical and business performance. Coverage includes Staffing the scalable organization: essential organizational, management, and leadership skills for technical leaders Building processes for scale: process lessons from hyper-growth companies, from technical issue resolution to crisis management Making better “build versus buy” decisions Architecting scalable solutions: powerful proprietary models for identifying scalability needs and choosing the best approaches to meet them Optimizing performance through caching, application and database splitting, and asynchronous design Scalability techniques for emerging technologies, including clouds and grids Planning for rapid data growth and new data centers Evolving monitoring strategies to tightly align with customer requirements

Download or read book Big Data written by Nathan Warren and published by . This book was released on 2015 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built. About the Book Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive. Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases. This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. What's Inside Introduction to big data systems Real-time processing of web-scale data Tools like Hadoop, Cassandra, and Storm Extensions to traditional database skills About the Authors Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing.

Download or read book Real Time Phoenix written by Stephen Bussey and published by Pragmatic Bookshelf. This book was released on 2020-03-25 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: Give users the real-time experience they expect, by using Elixir and Phoenix Channels to build applications that instantly react to changes and reflect the application's true state. Learn how Elixir and Phoenix make it easy and enjoyable to create real-time applications that scale to a large number of users. Apply system design and development best practices to create applications that are easy to maintain. Gain confidence by learning how to break your applications before your users do. Deploy applications with minimized resource use and maximized performance. Real-time applications come with real challenges - persistent connections, multi-server deployment, and strict performance requirements are just a few. Don't try to solve these challenges by yourself - use a framework that handles them for you. Elixir and Phoenix Channels provide a solid foundation on which to build stable and scalable real-time applications. Build applications that thrive for years to come with the best-practices found in this book. Understand the magic of real-time communication by inspecting the WebSocket protocol in action. Avoid performance pitfalls early in the development lifecycle with a catalog of common problems and their solutions. Leverage GenStage to build a data pipeline that improves scalability. Break your application before your users do and confidently deploy them. Build a real-world project using solid application design and testing practices that help make future changes a breeze. Create distributed apps that can scale to many users with tools like Phoenix Tracker. Deploy and monitor your application with confidence and reduce outages. Deliver an exceptional real-time experience to your users, with easy maintenance, reduced operational costs, and maximized performance, using Elixir and Phoenix Channels. What You Need: You'll need Elixir 1.9+ and Erlang/OTP 22+ installed on a Mac OS X, Linux, or Windows machine.

Download or read book Understanding Big Data Scalability written by Cory Isaacson and published by Prentice Hall. This book was released on 2014-07-11 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get Started Scaling Your Database Infrastructure for High-Volume Big Data Applications “Understanding Big Data Scalability presents the fundamentals of scaling databases from a single node to large clusters. It provides a practical explanation of what ‘Big Data’ systems are, and fundamental issues to consider when optimizing for performance and scalability. Cory draws on many years of experience to explain issues involved in working with data sets that can no longer be handled with single, monolithic relational databases.... His approach is particularly relevant now that relational data models are making a comeback via SQL interfaces to popular NoSQL databases and Hadoop distributions.... This book should be especially useful to database practitioners new to scaling databases beyond traditional single node deployments.” —Brian O’Krafka, software architect Understanding Big Data Scalability presents a solid foundation for scaling Big Data infrastructure and helps you address each crucial factor associated with optimizing performance in scalable and dynamic Big Data clusters. Database expert Cory Isaacson offers practical, actionable insights for every technical professional who must scale a database tier for high-volume applications. Focusing on today’s most common Big Data applications, he introduces proven ways to manage unprecedented data growth from widely diverse sources and to deliver real-time processing at levels that were inconceivable until recently. Isaacson explains why databases slow down, reviews each major technique for scaling database applications, and identifies the key rules of database scalability that every architect should follow. You’ll find insights and techniques proven with all types of database engines and environments, including SQL, NoSQL, and Hadoop. Two start-to-finish case studies walk you through planning and implementation, offering specific lessons for formulating your own scalability strategy. Coverage includes Understanding the true causes of database performance degradation in today’s Big Data environments Scaling smoothly to petabyte-class databases and beyond Defining database clusters for maximum scalability and performance Integrating NoSQL or columnar databases that aren’t “drop-in” replacements for RDBMSes Scaling application components: solutions and options for each tier Recognizing when to scale your data tier—a decision with enormous consequences for your application environment Why data relationships may be even more important in non-relational databases Why virtually every database scalability implementation still relies on sharding, and how to choose the best approach How to set clear objectives for architecting high-performance Big Data implementations The Big Data Scalability Series is a comprehensive, four-part series, containing information on many facets of database performance and scalability. Understanding Big Data Scalability is the first book in the series. Learn more and join the conversation about Big Data scalability at bigdatascalability.com.

Download or read book Fast and Scalable Cloud Data Management written by Felix Gessert and published by Springer Nature. This book was released on 2020-05-15 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: The unprecedented scale at which data is both produced and consumed today has generated a large demand for scalable data management solutions facilitating fast access from all over the world. As one consequence, a plethora of non-relational, distributed NoSQL database systems have risen in recent years and today’s data management system landscape has thus become somewhat hard to overlook. As another consequence, complex polyglot designs and elaborate schemes for data distribution and delivery have become the norm for building applications that connect users and organizations across the globe – but choosing the right combination of systems for a given use case has become increasingly difficult as well. To help practitioners stay on top of that challenge, this book presents a comprehensive overview and classification of the current system landscape in cloud data management as well as a survey of the state-of-the-art approaches for efficient data distribution and delivery to end-user devices. The topics covered thus range from NoSQL storage systems and polyglot architectures (backend) over distributed transactions and Web caching (network) to data access and rendering performance in the client (end-user). By distinguishing popular data management systems by data model, consistency guarantees, and other dimensions of interest, this book provides an abstract framework for reasoning about the overall design space and the individual positions claimed by each of the systems therein. Building on this classification, this book further presents an application-driven decision guidance tool that breaks the process of choosing a set of viable system candidates for a given application scenario down into a straightforward decision tree.

Download or read book Azure SQL Hyperscale Revealed written by Zoran Barać and published by Apress. This book was released on 2023-04-13 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take a deep dive into the Azure SQL Database Hyperscale Service Tier and discover a new form of cloud architecture from Microsoft that supports massive databases. The new horizontally scalable architecture, formerly code-named Socrates, allows you to decouple compute nodes from storage layers. This radically different approach dramatically increases the scalability of the service. This book shows you how to leverage Hyperscale to provide next-level scalability, high throughput, and fast performance from large databases in your environment. The book begins by showing how Hyperscale helps you eliminate many of the problems of traditional high-availability and disaster recovery architecture. You’ll learn how Hyperscale overcomes storage capacity limitations and issues with scale-up times and costs. With Hyperscale, your costs do not increase linearly with database size and you can manage more data than ever at a lower cost. The book teaches you how to deploy, configure, and monitor an Azure SQL Hyperscale database in a production environment. The book also covers migrating your current workloads from traditional architecture to Azure SQL Hyperscale. What You Will Learn Understand the advantages of Hyperscale over traditional architecture Deploy a Hyperscale database on the Azure cloud (interactively and with code) Configure the advanced features of the Hyperscale database tier Monitor and scale database performance to suit your needs Back up and restore your Azure SQL Hyperscale databases Implement disaster recovery and failover capability Compare performance of Hyperscale vs traditional architecture Migrate existing databases to the Hyperscale service tier Who This Book Is For SQL architects, data engineers, and DBAs who want the most efficient and cost-effective cloud technologies to run their critical data workloads, and those seeking rapid scalability and high performance and throughput while utilizing large databases

Download or read book Designing Big Data Platforms written by Yusuf Aytas and published by John Wiley & Sons. This book was released on 2021-07-08 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: DESIGNING BIG DATA PLATFORMS Provides expert guidance and valuable insights on getting the most out of Big Data systems An array of tools are currently available for managing and processing data—some are ready-to-go solutions that can be immediately deployed, while others require complex and time-intensive setups. With such a vast range of options, choosing the right tool to build a solution can be complicated, as can determining which tools work well with each other. Designing Big Data Platforms provides clear and authoritative guidance on the critical decisions necessary for successfully deploying, operating, and maintaining Big Data systems. This highly practical guide helps readers understand how to process large amounts of data with well-known Linux tools and database solutions, use effective techniques to collect and manage data from multiple sources, transform data into meaningful business insights, and much more. Author Yusuf Aytas, a software engineer with a vast amount of big data experience, discusses the design of the ideal Big Data platform: one that meets the needs of data analysts, data engineers, data scientists, software engineers, and a spectrum of other stakeholders across an organization. Detailed yet accessible chapters cover key topics such as stream data processing, data analytics, data science, data discovery, and data security. This real-world manual for Big Data technologies: Provides up-to-date coverage of the tools currently used in Big Data processing and management Offers step-by-step guidance on building a data pipeline, from basic scripting to distributed systems Highlights and explains how data is processed at scale Includes an introduction to the foundation of a modern data platform Designing Big Data Platforms: How to Use, Deploy, and Maintain Big Data Systems is a must-have for all professionals working with Big Data, as well researchers and students in computer science and related fields.

Download or read book Web Scalability for Startup Engineers written by Artur Ejsmont and published by McGraw Hill Professional. This book was released on 2015-07-03 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: This invaluable roadmap for startup engineers reveals how to successfully handle web application scalability challenges to meet increasing product and traffic demands. Web Scalability for Startup Engineers shows engineers working at startups and small companies how to plan and implement a comprehensive scalability strategy. It presents broad and holistic view of infrastructure and architecture of a scalable web application. Successful startups often face the challenge of scalability, and the core concepts driving a scalable architecture are language and platform agnostic. The book covers scalability of HTTP-based systems (websites, REST APIs, SaaS, and mobile application backends), starting with a high-level perspective before taking a deep dive into common challenges and issues. This approach builds a holistic view of the problem, helping you see the big picture, and then introduces different technologies and best practices for solving the problem at hand. The book is enriched with the author's real-world experience and expert advice, saving you precious time and effort by learning from others' mistakes and successes. Language-agnostic approach addresses universally challenging concepts in Web development/scalability—does not require knowledge of a particular language Fills the gap for engineers in startups and smaller companies who have limited means for getting to the next level in terms of accomplishing scalability Strategies presented help to decrease time to market and increase the efficiency of web applications

Download or read book The Art of Scalability written by Martin L. Abbott and published by Addison-Wesley Professional. This book was released on 2015-05-23 with total page 1148 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Comprehensive, Proven Approach to IT Scalability–Updated with New Strategies, Technologies, and Case Studies In The Art of Scalability, Second Edition, leading scalability consultants Martin L. Abbott and Michael T. Fisher cover everything you need to know to smoothly scale products and services for any requirement. This extensively revised edition reflects new technologies, strategies, and lessons, as well as new case studies from the authors’ pioneering consulting practice, AKF Partners. Writing for technical and nontechnical decision-makers, Abbott and Fisher cover everything that impacts scalability, including architecture, process, people, organization, and technology. Their insights and recommendations reflect more than thirty years of experience at companies ranging from eBay to Visa, and Salesforce.com to Apple. You’ll find updated strategies for structuring organizations to maximize agility and scalability, as well as new insights into the cloud (IaaS/PaaS) transition, NoSQL, DevOps, business metrics, and more. Using this guide’s tools and advice, you can systematically clear away obstacles to scalability–and achieve unprecedented IT and business performance. Coverage includes • Why scalability problems start with organizations and people, not technology, and what to do about it • Actionable lessons from real successes and failures • Staffing, structuring, and leading the agile, scalable organization • Scaling processes for hyper-growth environments • Architecting scalability: proprietary models for clarifying needs and making choices–including 15 key success principles • Emerging technologies and challenges: data cost, datacenter planning, cloud evolution, and customer-aligned monitoring • Measuring availability, capacity, load, and performance