InfluxData and the TICK stack for IoT data streaming
With every advancement in technology we get a new database to get excited about. With the cloud, we started caring about scale, and No-SQL databases rose to the fore. With social networks, graph databases became the hot new thing. And now, with the internet of things, time series databases are getting their day in the sun.
That’s why InfluxData just raised $ 35 million in a round led by Sapphire Ventures. The goal is to expand the company’s database sales beyond its current customers, which include Tesla, IBM, and Nordstrom. At the end of January, another time series database called Timescale raised $ 12.4 million in funding. So the space is hot.
Time series databases aren’t new. Traditionally, they are simply a measurement of the state of some sensor and the time. But now that there are connected sensors that can take in data hundreds of times a day or more, these databases are seeing more action. Plus, in many situations it’s not enough to collect the data and then ship it somewhere as a log. Now people want to take action on that data. And they want to take that action as soon as possible.
This means that time series databases aren’t just handling a greater velocity and volume of data; they also have to analyze it as it streams by. Think of it as the more active version of logging data as performed by companies such as Splunk. There are many time series databases out there, including giants such as GE’s Predix, as well as smaller projects like Riak or Graphite. Many projects started as ways to monitor IT systems and websites, not thermostat readings or automotive data.
In InfluxData’s case, CEO Evan Kaplan touts the speed of the database plus the available suite of tools it works with, which allows developers to monitor IoT assets and query data even as more data is coming in. It also stores data in a compressed format and quickly ditches the dregs it doesn’t need.
Together with tools called Telegraf, Chronograf, and Kapacitor, Kaplan is selling a concept called the TICK stack. It is designed to rapidly ingest and handle data while also giving users the tools to query it. As a lover of many IT stacks—from the historical LAMP (Linux, Apache, MySQL, PHP) stack for web development to the more recent SMACK (Spark, Mesos, Akka, Cassandra, and Kafka) stack for big data—I like the idea of one for the IoT.
However, note that in this case Influx is promoting the tools it is developing as opposed to developers promoting a collection of independent technologies that they have found to work well together. That doesn’t mean it will fail; it’s just a different genesis.
As for revenue, InfluxData has a slightly different model than the traditional open-source efforts. It offers one server for free, and as the database expands, customers will pay for an enterprise license so they can build a larger cluster capable of handling more. Given how much time series data machines throw off, it’s a model that should net it plenty of revenue over time.