Time Series Databases


Book Description

Time series data is of growing importance, especially with the rapid expansion of the Internet of Things. This concise guide shows you effective ways to collect, persist, and access large-scale time series data for analysis. You'll explore the theory behind time series databases and learn practical methods for implementing them. Authors Ted Dunning and Ellen Friedman provide a detailed examination of open source tools such as OpenTSDB and new modifications that greatly speed up data ingestion. You'll learn: A variety of time series use cases The advantages of NoSQL databases for large-scale time series data NoSQL table design for high-performance time series databases The benefits and limitations of OpenTSDB How to access data in OpenTSDB using R, Go, and Ruby How time series databases contribute to practical machine learning projects How to handle the added complexity of geo-temporal data For advice on analyzing time series data, check out Practical Machine Learning: A New Look at Anomaly Detection, also from Ted Dunning and Ellen Friedman.




Data Mining in Time Series Databases


Book Description

Adding the time dimension to real-world databases produces Time SeriesDatabases (TSDB) and introduces new aspects and difficulties to datamining and knowledge discovery. This book covers the state-of-the-artmethodology for mining time series databases. The novel data miningmethods presented in the book include techniques for efficientsegmentation, indexing, and classification of noisy and dynamic timeseries. A graph-based method for anomaly detection in time series isdescribed and the book also studies the implications of a novel andpotentially useful representation of time series as strings. Theproblem of detecting changes in data mining models that are inducedfrom temporal databases is additionally discussed.




A Comparison of NoSQL Time Series Databases


Book Description

Research Paper (undergraduate) from the year 2015 in the subject Engineering - Industrial Engineering and Management, grade: 1,0, Technical University of Berlin (Wirtschaftsinformatik - Information Systems Engineering (ISE)), course: Seminar: Hot Topics in Information Systems Engineering, language: English, abstract: During the last years NoSQL databases have been developed to ad-dress the needs of tremendous performance, reliability and horizontal scalability. NoSQL time series databases (TSDBs) have risen to combine valuable NoSQL properties with characteristics of time series data encountering many use-cases. Solutions offer the efficient handling of data volume and frequency related to time series. Developers and decision makers struggle with the choice of a TSDB among a large variety of solutions. Up to now no comparison exists focusing on the specific features and qualities of those heterogeneous applications. This paper aims to deliver two frameworks for the comparison of TSDBs, firstly with a focus on features and secondly on quality. Furthermore, we apply and evaluate the frameworks on up to seven open-source TSDBs such as InfluxDB and OpenTSDB. We come to the result that the investigated TSDBs differ mainly in support- and extension related points. They share performance-enhancing techniques, time-related query capabilities and data schemas optimized for the handling of time-series data.




Solving Business Problems with Informix TimeSeries


Book Description

The world is becoming more and more instrumented, interconnected, and intelligent in what IBM® terms a smarter planet, with more and more data being collected for analysis. In trade magazines, this trend is called big data. As part of this trend, the following types of time-based information are collected: Large data centers support a corporation or provide cloud services. These data centers need to collect temperature, humidity, and other types of information over time to optimize energy usage. Utility meters (referred to as smart meters) allow utility companies to collect information over a wireless network and to collect more data than ever before. IBM Informix® TimeSeries is optimized for the processing of time-based data and can provide the following benefits: Storage savings: Storage can be optimized when you know the characteristics of your time-based data. Informix TimeSeries often uses one third of the storage space that is required by a standard relational database. Query performance: Informix TimeSeries takes into consideration the type of data to optimize its organization on disk and eliminates the need for some large indexes and additional sorting. For these reasons and more, some queries can easily have an order of magnitude performance improvement compared to standard relational. Simpler queries: Informix TimeSeries includes a large set of specialized functions that allow you to better express the processing that you want to execute. It even provides a toolkit so that you can add proprietary algoritms to the library. This IBM Redbooks® publication is for people who want to implement a solution that revolves around time-based data. It gives you the information that you need to get started and be productive with Informix TimeSeries.




The Comprehensive Guide to Databases


Book Description

The Comprehensive Guide to Databases offers an in-depth exploration into the dynamic world of database technology. This guide is designed for a wide audience, from beginners to seasoned professionals, aiming to enhance their understanding of database management. It covers the foundations of database technology, including relational databases, NoSQL solutions, and advanced topics such as distributed systems, big data analytics, and the role of AI and machine learning in database management. With detailed explanations of key concepts, practical applications, and real-world case studies, this book provides readers with the skills necessary to design, implement, and manage database systems effectively. The guide also looks toward the future of database technology, examining emerging trends like cloud databases, data security, and regulatory compliance, making it an essential resource for anyone looking to master the art of database management in the modern digital landscape.




Encyclopedia of Database Technologies and Applications


Book Description

"Addresses the evolution of database management, technologies and applications along with the progress and endeavors of new research areas."--P. xiii.




Advances in Databases: Concepts, Systems and Applications


Book Description

This book constitutes the refereed proceedings of the 12th International Conference on Database Systems for Advanced Applications, DASFAA 2007, held in Bangkok, Thailand, April 2007. Coverage includes query language and query optimization, data mining and knowledge discovery, P2P and grid-based data management, XML databases, database modeling and information retrieval, Web and information retrieval, database applications and security.




Databases Theory and Applications


Book Description

This book constitutes the refereed proceedings of the 28th Australasian Database Conference, ADC 2017, held in Brisbane, QLD, Australia, in September 2017. The 20 full papers presented together with 2 demo papers were carefully reviewed and selected from 32 submissions. The mission of ADC is to share novel research solutions to problems of today’s information society that fulfill the needs of heterogeneous applications and environments and to identify new issues and directions for future research and development work. The topics of the presented papers are related to all practical and theoretical aspects of advanced database theory and applications, as well as case studies and implementation experiences.




SQL and NoSQL Databases


Book Description

This textbook offers a comprehensive introduction to relational (SQL) and non-relational (NoSQL) databases. The authors thoroughly review the current state of database tools and techniques and examine upcoming innovations. In the first five chapters, the authors analyze in detail the management, modeling, languages, security, and architecture of relational databases, graph databases, and document databases. Moreover, an overview of other SQL- and NoSQL-based database approaches is provided. In addition to classic concepts such as the entity and relationship model and its mapping in SQL database schemas, query languages or transaction management, other aspects for NoSQL databases such as non-relational data models, document and graph query languages (MQL, Cypher), the Map/Reduce procedure, distribution options (sharding, replication) or the CAP theorem (Consistency, Availability, Partition Tolerance) are explained. This 2nd English edition offers a new in-depth introduction to document databases with a method for modeling document structures, an overview of the document-oriented MongoDB query language MQL as well as security and architecture aspects. The topic of database security is newly introduced as a separate chapter and analyzed in detail with regard to data protection, integrity, and transactions. Texts on data management, database programming, and data warehousing and data lakes have been updated. In addition, the book now explains the concepts of JSON, JSON schema, BSON, index-free neighborhood, cloud databases, search engines and time series databases. The book includes more than 100 tables, examples and illustrations, and each chapter offers a list of resources for further reading. It conveys an in-depth comparison of relational and non-relational approaches and shows how to undertake development for big data applications. This way, it benefits students and practitioners working across the broad field of data science and applied information technology.




Database and Expert Systems Applications


Book Description

This book constitutes the refereed proceedings of the 21 International Conference on Database and Expert Systems Applications, DEXA 2010, held in Bilbao, Spain, August 30 - September 3, 2010. The 45 revised full papers and 36 short papers were carefully reviewed and selected from 197 submissions. The papers are organized in topical sections on Data Mining Systems, Parallelism and Query Planning, Data Warehousing and Decision Support Systems, Temporal, Spatial and High Dimensional Databases, Data Mining Algorithms, Information Retrieval, Query Processing and Optimization.