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A time series database is a software system that is optimized for storing and serving time series through associated pairs of time(s) and value(s). [1] In some fields, time series may be called profiles, curves, traces or trends. [ 2 ]
TimescaleDB is an open-source time series database [3] [4] [5] developed by Timescale Inc. It is written in C and extends PostgreSQL. [6] [7] TimescaleDB is a relational database [8] and supports standard SQL queries. Additional SQL functions and table structures provide support for time series data oriented towards storage, performance, and ...
RRDtool (round-robin database tool) aims to handle time series data such as network bandwidth, temperatures or CPU load. The data is stored in a circular buffer based database, thus the system storage footprint remains constant over time. It also includes tools to extract round-robin data in a graphical format, for which it was originally intended.
Apache IoTDB is a column-oriented open-source, time-series database (TSDB) management system written in Java. [1] It has both edge and cloud versions, provides an optimized columnar file format for efficient time-series data storage, and TSDB with high ingestion rate, low latency queries and data analysis support.
In manufacturing, an operational historian is a time-series database application that is developed for operational process data. [1] Historian software is often embedded or used in conjunction with standard DCS and PLC control systems to provide enhanced data capture, validation, compression, and aggregation capabilities. [2]
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The Portable Document Format (PDF) is a file format used to present documents in a manner independent of application software, hardware, and operating systems. Each PDF file encapsulates a complete description of the presentation of the document, including the text, fonts, graphics, and other information needed to display it.
A time series measures the progression of one or more quantities over time. For instance, the figure above shows the level of water in the Nile river between 1870 and 1970. Change point detection is concerned with identifying whether, and if so when, the behavior of the series changes significantly. In the Nile river example, the volume of ...