TL; DR: InfluxData’s time-series database, InfluxDB, was purpose-built to handle the vast amount of time-stamped data created by today’s apps, sensors, and digital infrastructure. The scalable data ingestion engine empowers developers to collect, store, monitor, and visualize time-series data. Now, with InfluxDB Cloud, InfluxData is meeting developers where they are in terms of hosting — whether that means AWS, Azure, or Google Cloud.
In a digital scene chock-full of relational and NoSQL data models, a different flavor of databases is quickly growing in popularity: the time-series database. Unlike traditional databases that process data in batches, these databases do so in real time, and each entry is associated with a timestamp.
According to DB-Engines, time-series models currently represent the fastest-growing category in the database industry — and for good reason: The digital world now churns out astronomical amounts of data. The World Economic Forum estimates that by 2025, the amount of data generated each day will reach 463 Exabytes globally.
Time-series databases prove particularly beneficial in this environment, allowing organizations to leverage large, high-frequency data streams in various beneficial scenarios.
“Think about all the horizontal scale-out that people are doing in the cloud — as applications and services get bigger, they’re being spun up in more regions on AWS, Azure, and Google. And each deployment is handling a bigger and bigger workload,” said Brian Mullen, Chief Marketing Officer at InfluxData. “It’s the same on the IoT side, where you have more devices and sensors coming online. And it’s all happening at scale.”
InfluxDB, InfluxData’s time-series database, is the most popular of its kind on the market based on data from DB-Engines. The scalable data ingestion engine was purpose-built to collect, store, monitor, and visualize massive quantities of time-stamped data.
The company offers the time-series platform via both InfluxDB Enterprise and the serverless InfluxDB Cloud, available on AWS, Azure, and Google Cloud Platform (GCP).
A Highly Scalable Data Ingestion and Storage Engine
InfluxData Founder Paul Dix founded InfluxData through Y Combinator in 2012.
While working on the project, Paul started looking for a turnkey time-series engine. After coming up empty-handed, he built an open-source solution himself.
“He was so frustrated with the whole process that he decided to help other developers by open-sourcing what he had built,” Brian said. “That became InfluxDB, and we were kind of off to the races from there.”
Later, the company received Series A funding from Trinity Ventures and Mayfield, which helped the team build out additional parts of its tech stack. Today, the San Francisco-based company is backed by several investors, including Battery Ventures, Sapphire Ventures, and Y Combinator, with employees distributed throughout the U.S. and Europe.
“InfluxDB was the foundation of everything,” Brian told us. “Then we built out Telegraph, a collection agent, and extended InfluxDB to include a visualization and administrative tool and notification engine. The product is built from the ground up to focus on the unique aspects of time-series data, creating a specialized product for large volumes of data.”
“You’re dealing with data that’s coming in as quickly as you’re dumping it out on the back end,” Brian said. “And then you have a lot of context switching — you have to focus on the minutiae of the data that is coming in at a sub-second level in many cases, and you have to understand it in real time. But then the way that you store it might be downsampled considerably. So there’s a lot of flexibility required in terms of the minutiae and the aggregate.”
InfluxDB Cloud: Elastic, Serverless, and Cloud-Hosted
In 2016, InfluxData began selling its first commercial product: InfluxDB Enterprise. The product evolved the single-node capabilities of the open-source platform into a high availability (HA) solution. InfluxDB Enterprise can transform any InfluxData instance into a production-ready cluster that developers can run anywhere — including on-premises, in the private or public cloud, or at the network edge.
“With InfluxDB Enterprise, you have multiple nodes for scale-out purposes, redundancy, an enterprise cluster,” Brian said. “We sell it on an annual nodes-and-cores basis.”
From 2016 onward, InfluxData began to zero in on the commercial side of the business, which culminated with the launch of InfluxDB Cloud in 2019. The elastic, cloud-hosted solution empowers developers to build software on an easy-to-use time-series platform available on AWS, Azure, and Google Cloud. And it’s free to get started with a transparent, usage-based pricing model.
“InfluxDB Cloud is a multitenant service where people can just pick an endpoint and run time-series data into our platform,” Brian said. “They pay using three basic vectors: inbound data, the total volume of query counts, and storage.”
Use cases for InfluxDB CLoud include predictive analytics in finance, fleet management, and the industrial IoT.
“Whether they’re staff engineers, product managers, or what have you, many of these folks are actually building net-new products rather than operating something built by somebody else,” Brian said. “And so the features and the product are really oriented toward helping people in the construction of applications.”
Fostering a Faster Time to Awesome™
We’ve all heard of time to market (TTM), a parameter of business agility that gauges the length of time it takes product conception to public availability. InfluxData’s value proposition centers on a similar idea — but from the developers’ perspective.
“It is the biggest thing that we focus on — the thesis of the product — is what Paul calls Time to Awesome™,” Brian said. “The concept is that the faster developers can get up and running with a product that they’re using, the better it’s going to be for them.”
Part of offering a streamlined solution is making it easy to ingest data, as InfluxData Product Manager Samantha Wang demonstrates in this video showing how to ingest data in five easy steps.
“We really want to give developers a service they feel confident in, that they can get up and running very quickly. And they should be able to do that using our self-service account and documentation without talking to a human. We’re of course here and have a sales team and an onboarding team and support team to help people as needed, but we don’t expect that they need human intervention.”
InfluxData’s tools are designed to be used quickly and easily in a self-sufficient manner.
“We don’t think it’s a great thing if you’re sitting there, working on your influx stuff for days or weeks at a time,” Brian said. “If you think about it from a builder’s perspective, the less time that they have to deal with our stuff, the better.”
Building a Customer-Focused Culture
On that note, one of InfluxData’s primary goals moving forward is to meet developers where they are in terms of cloud platforms, purchasing options, and cloud regions.
“We’re multicloud, so we have the service available on AWS, Azure, and Google, and each of those is an ecosystem unto itself,” Brian said. “We’ve also launched our service on marketplaces so that you can buy either directly from us or through those marketplaces.”
The same applies to physical cloud regions with unique InfluxDB Cloud URLs and API endpoints.
“We’re in North America and Europe today; we’ll be adding the Asia Pacific and some other regions in the near future,” Brian said.