Time Series Databases

New Ways to Store and Access Data

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Book Description

Time series databases enable a fundamental step in the central storage and analysis of many types of machine data. As such, they lie at the heart of the Internet of Things (IoT). There's a revolution in sensor - to - insight data flow that is rapidly changing the way we perceive and understand the world around us. Much of the data generated by sensors, as well as a variety of other sources, benefits from being collected as time series.

Although the idea of collecting and analyzing time series data is not new, the astounding scale of modern datasets, the velocity of data accumulation in many cases, and the variety of new data sources together contribute to making the current task of building scalable time series databases a huge challenge. A new world of time series data calls for new approaches and new tools.

The huge volume of data to be handled by modern time series databases (TSDB) calls for scalability. Systems like Apache Cassandra, Apache HBase, MapR-DB, and other NoSQL databases are built for this scale, and they allow developers to scale relatively simple applications to extraordinary levels. In this book, we show you how to build scalable, high-performance time series databases using open source software on top of Apache HBase or MapR-DB. We focus on how to collect, store, and access large-scale time series data rather than the methods for analysis.

This book is published as open-access, which means it is freely available to read, download, and share without restrictions.

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