Real-time applications are becoming the norm today. But building a model that works properly requires real-time data from the source, in-flight stream processing, and low latency serving of its analytics. With this practical book, data engineers, data architects, and data analysts will learn how to use streaming databases to build real-time solutions. Authors Hubert Dulay and Ralph M. Debusmann take you through streaming database fundamentals, including how these databases reduce infrastructure for real-time solutions. You'll learn the difference between streaming databases, stream processing, and real-time online analytical processing (OLAP) databases. And you'll discover when to use push queries versus pull queries, and how to serve synchronous and asynchronous data emanating from streaming databases. This guide helps you: Explore stream processing and streaming databases Learn how to build a real-time solution with a streaming database Understand how to construct materialized views from any number of streams Learn how to serve synchronous and asynchronous data Get started building low-complexity streaming solutions with minimal setup

Summary Streaming Data introduces the concepts and requirements of streaming and real-time data systems. The book is an idea-rich tutorial that teaches you to think about how to efficiently interact with fast-flowing data. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology As humans, we're constantly filtering and deciphering the information streaming toward us. In the same way, streaming data applications can accomplish amazing tasks like reading live location data to recommend nearby services, tracking faults with machinery in real time, and sending digital receipts before your customers leave the shop. Recent advances in streaming data technology and techniques make it possible for any developer to build these applications if they have the right mindset. This book will let you join them. About the Book Streaming Data is an idea-rich tutorial that teaches you to think about efficiently interacting with fast-flowing data. Through relevant examples and illustrated use cases, you'll explore designs for applications that read, analyze, share, and store streaming data. Along the way, you'll discover the roles of key technologies like Spark, Storm, Kafka, Flink, RabbitMQ, and more. This book offers the perfect balance between big-picture thinking and implementation details. What's Inside The right way to collect real-time data Architecting a streaming pipeline Analyzing the data Which technologies to use and when About the Reader Written for developers familiar with relational database concepts. No experience with streaming or real-time applications required. About the Author Andrew Psaltis is a software engineer focused on massively scalable real-time analytics. Table of Contents PART 1 - A NEW HOLISTIC APPROACH Introducing streaming data Getting data from clients: data ingestion Transporting the data from collection tier: decoupling the data pipeline Analyzing streaming data Algorithms for data analysis Storing the analyzed or collected data Making the data available Consumer device capabilities and limitations accessing the data PART 2 - TAKING IT REAL WORLD Analyzing Meetup RSVPs in real time

This book constitutes the refereed proceedings of the 8th International Symposium on Spatial and Temporal Databases, SSTD 2003, held at Santorini Island, Greece in July 2003. The 28 revised full papers presented together with a keynote paper were carefully reviewed and selected from 105 submissions. the papers are organized in topical sections on access methods, advanced query processing, data mining and data warehousing, distance-based queries, mobility and moving points management, modeling and languages, similarity processing, systems and implementation issues.

Oracle is an enormous system, with myriad technologies, options, and releases. Most users--even experienced developers and database administrators--find it difficult to get a handle on the full scope of the Oracle database. And, as each new Oracle version is released, users find themselves under increasing pressure to learn about a whole range of new technologies. The latest challenge is Oracle Database 11g. This book distills an enormous amount of information about Oracle into a compact, easy-to-read volume filled with focused text, illustrations, and helpful hints. It contains chapters on: Oracle products, options, data structures, and overall architecture for Oracle Database 11g, as well as earlier releases (Oracle Database 10g, Oracle9i, and Oracle8i) Installing, running, managing, monitoring, networking, and tuning Oracle, including Enterprise Manager (EM) and Oracle's self-tuning and management capabilities; and using Oracle security, auditing, and compliance (a new chapter in this edition) Multiuser concurrency, data warehouses, distributed databases, online transaction processing (OLTP), high availability, and hardware architectures (e.g., SMP, clusters, NUMA, and grid computing) Features beyond the Oracle database: Oracle Application Express, Fusion Middleware (including Oracle Application Server), and database SOA support as a Web services provider The latest Oracle Database 11g features: query result set caching, Automatic Memory Management, the Real Application Testing, Advanced Compression, Total Recall, and Active Data Guard Option Options, changes to the OLAP Option (transparently accessed and managed as materialized views), the Flashback transaction command, transparent data encryption, the Support Workbench (and diagnosability infrastructure), and partitioning enhancements (including interval and new composite types) For new Oracle users, DBAs, developers, and managers, Oracle Essentials provides an invaluable, all-in-one introduction to the full range of Oracle features and technologies, including the just-released Oracle Database 11g features. But even if you already have a library full of Oracle documentation, you'll find that this compact book is the one you turn to, again and again, as your one-stop, truly essential reference. "Oracle Essentials gives a clear explanation of the key database concepts and architecture underlying the Oracle database. It's a great reference for anyone doing development or management of Oracle databases." --Andrew Mendelsohn, Senior Vice President, Database Server Technologies, Oracle Corporation

Gain deep insight into real-time analytics, including the features of these systems and the problems they solve. With this practical book, data engineers at organizations that use event-processing systems such as Kafka, Google Pub/Sub, and AWS Kinesis will learn how to analyze data streams in real time. The faster you derive insights, the quicker you can spot changes in your business and act accordingly. Author Mark Needham from StarTree provides an overview of the real-time analytics space and an understanding of what goes into building real-time applications. The book's second part offers a series of hands-on tutorials that show you how to combine multiple software products to build real-time analytics applications for an imaginary pizza delivery service. You will: Learn common architectures for real-time analytics Discover how event processing differs from real-time analytics Ingest event data from Apache Kafka into Apache Pinot Combine event streams with OLTP data using Debezium and Kafka Streams Write real-time queries against event data stored in Apache Pinot Build a real-time dashboard and order tracking app Learn how Uber, Stripe, and Just Eat use real-time analytics

This book constitutes the proceedings of the 16th IFIP TC8 International Conference on Computer Information Systems and Industrial Management, CISIM 2017, held in Bialystok, Poland, in June 2017. The 60 regular papers presented together with 5 keynotes were carefully reviewed and Selected from 85 submissions. They are organized in the following topical sections: algorithms; biometrics and pattern recognition applications; data analysis and information retrieval; engineering of enterprise software products; industrial management and other applications; modelling and optimization; various aspects of computer security.

Streaming data is a big deal in big data these days. As more and more businesses seek to tame the massive unbounded data sets that pervade our world, streaming systems have finally reached a level of maturity sufficient for mainstream adoption. With this practical guide, data engineers, data scientists, and developers will learn how to work with streaming data in a conceptual and platform-agnostic way. Expanded from Tyler Akidau’s popular blog posts "Streaming 101" and "Streaming 102", this book takes you from an introductory level to a nuanced understanding of the what, where, when, and how of processing real-time data streams. You’ll also dive deep into watermarks and exactly-once processing with co-authors Slava Chernyak and Reuven Lax. You’ll explore: How streaming and batch data processing patterns compare The core principles and concepts behind robust out-of-order data processing How watermarks track progress and completeness in infinite datasets How exactly-once data processing techniques ensure correctness How the concepts of streams and tables form the foundations of both batch and streaming data processing The practical motivations behind a powerful persistent state mechanism, driven by a real-world example How time-varying relations provide a link between stream processing and the world of SQL and relational algebra

An encyclopedia designed especially to meet the needs of elementary, junior high, and senior high school students.