In today’s world, one cannot sufficiently emphasize the importance of real-time data collection, management, and analytics. Such time series data isn’t just the fuel for IoT but its backbone as well, and you simply cannot ignore it. After all, these are tools that help you manage data, improve operations, provide better customer service, and create personalized marketing campaigns – ultimately, to help you increase your revenue and profits as a business owner.

What’s time series data, and why does it matter?

It is a sequence of data points where the same variable takes different values across a period. This could be as short as a few milliseconds or as long as several years. It could be regular (for instance, periodic CPU performance checks) or irregular (time series data logged every time an event occurs, such as a door opening).

Self-driving cars, for instance, use time series data, to continuously collect data about their changing environment. Increasingly more and more businesses are reliant on time series data. 

Whether it’s stock trading algorithms, smart homes, or even air quality monitoring systems… if you need lightning-fast data collection and analytics, time series data is the way to go.

It’s primarily used for real-time analytics (for instance, the footage in security cameras) and in DevOps (for real-time monitoring of servers and applications).

InfluxDB: The time series database

InfluxDB is an open-source time series database purpose-built for time series data. It is essentially designed to store large volumes of time series data and quickly perform real-time analysis on that data.

Developed by InfluxData, this application is written in the Go programming language for storage and retrieval of time series data in fields such as operations monitoring, application metrics, and Internet of Things sensor data.

How can InfluxDB help your business?

Let’s take a real-life example of Trivago, an online hotel booking service. They say metrics are being sent from around 150 clients within a 10-second interval. Their InfluxDB receives 10K values/sec at a rate of 1.2MB/sec and has been storing data from more than 1.6 million series in just three months. 

That’s an incredible amount of time series data being stored using InfluxDB, made possible by the fact that InfluxDB is purpose-built for time series data.

Here are four reasons why you should use InfluxDB if you aren’t already.

1. It is a scalable read-and-write time series database
2. It is optimized for fast search and retrieval of time series data
3. It offers a schema-less database, meaning that you can add any field at any time, even after the initial development stage
4. It also provides data visualization in the form of live graphs (such the rise and fall of stock prices)

How does InfluxDB work?

InfluxDB works in tandem with Telegraf (also created by the same company, Influx Data), which is an open-source data collection agent for reporting metrics. Like InfluxDB, it is also written in Go with multiple plugin support options for data sources such as Amazon CloudWatch, Google Pub/Sub, Azure Event Hub, and so on.

Traditionally, relational databases fare poorly with very large datasets, but with InfluxDB and Telegraf, your database is built to handle and ingest a relentless stream of data without negative performance impact or lag, even as your application scales and data volume grows.

Want to get started with InfluxDB and transform your data collection, storage, and analytics? Talk to our team at CloudNow today.