A Time Series Database (TSDB) is a database optimized for time-stamped or time series data. Time series data are simply measurements or events that are tracked, monitored, downsampled, and aggregated over time. This could be server metrics, application performance monitoring, network data, sensor data, events, clicks, trades in a market, and many other types of analytics data.
A Time Series Database is built specifically for handling metrics and events or measurements that are time-stamped. A TSDB is optimized for measuring change over time. Properties that make time series data very different than other data workloads are data lifecycle management, summarization, and large range scans of many records.
The whole InfluxData platform is built from an open source core. InfluxData is an active contributor to the Telegraf, InfluxDB, Chronograf and Kapacitor (TICK) projects as well as selling InfluxEnterprise and InfluxCloud on this open source core. The InfluxDB data model is quite different from other time series solutions like Graphite, RRD, or OpenTSDB. InfluxDB has a line protocol for sending time series data which takes the following form: measurement-name tag-set field-set timestamp The measurement name is a string, the tag set is a collection of key/value pairs where all values are strings, and the field set is a collection of key/value pairs where the values can be int64, float64, bool, or string.
Read more —- InfluxDB | Installation | How To Use | Time Series Database ?
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SRE Monitoring • PayPal
Nearly every available surface in the physical world is being instrumented with sensors — streets, cars, factories, power grids, ice caps, satellites, clothing, phones, microwaves, milk containers, planets, even human bodies. This data is streaming in real time and will require companies to select an IoT data platform architecture that is resilient, scalable and extensible enough to handle these new workloads.
If businesses can properly harness all of this data, they can gain real-time insights, accelerate decision-making, perform automated tasks, and create value by enabling organizations to become data-driven.
IoT devices will generate more data than we have ever experienced. This data is streaming in real time and will force companies to determine which IoT data platform architecture will be resilient, scalable, and extensible enough to handle these new workloads.
Tracking battery performance, turbine production, package delivery status and generally visually monitoring sensor data provides incredible capabilities to the business and their customers. This is usually the first step in any successful IoT project.
Using historical data from sensors to gain insights that can be applied to the current situation creates a major competitive advantage. Predictive maintenance, optimized traffic routing, reduced churn management, and enhanced water conservation are all possible with IoT analytics.
With the speed and velocity of events being generated by sensors, businesses want to act on this data in real time with no human interaction. For example, automatically shutting down a pump if a leak is detected, or changing wind turbine direction based on wind speed, all create an immediate business advantage.
IoT data characteristics
IoT data is different from the data that typical application architectures and platforms have been created to solve. IoT data, or sensor data, has three unique characteristics:
IoT is synonymous with time-stamped data, or time series data since the purpose of any sensor is to measure change over time. To gain insight and act, systems need to evaluate and analyze the data based on timeframes and ranges. The modern IoT data platform needs to be optimized for time series data.
IoT is synonymous with streaming data. Data is created by a myriad of sensors, and each sensor emits a relentless stream of data. The modern IoT data platform needs to be optimized for streaming data and has actionable analytics to find the signal from all the noise.
Sensors capture and emit data in real time. Greater business value is derived if the data can also be interpreted and acted upon in real time. The modern IoT data platform is designed to handle real-time ingestion and real-time streaming analytics.
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