We are excited to announce that we are joining the InfluxData ecosystem. InfluxDB is the leading time series platform for storing test and measurement data. Marple can now be coupled to an InfluxDB database, giving engineers the power of both. In this blog post, we dive deeper into what the integration offers and how to set it up.

Engineers traditionally capture sensor data with loggers. Most of these devices store their data in files: csv, mat, tdms, hdf5, … But in recent years, we have seen our customers expand their workflows to also ingest it in time series databases, such as InfluxDB. Having the sensor output in a database gives a clean interface from which other tooling can consume the data. We believe this is a great step forward in opening up the data to web-based tooling for engineers.

But sensor data is a unique use case for InfluxDB. The data is time series, but it is often not one continuous stream of data. Measurements are frequently done as part of an ad hoc test or larger testing campaign. These tests typically have a start and end time and can be sampled as fast as 10 kHz. Visually analysing this kind of data asks for tooling that is highly interactive.

“We see engineering teams leaving behind file based workflows for storing sensor data. Time series databases provide a crucial role in this for opening up the data analysis ecosystem.” - Nero Vanbiervliet, CTO

Marple users that already have an InfluxDB instance can now benefit from a better workflow. The electric racing team of Delft is already streaming the data from their car to InfluxDB. In the past, they used to export from InfluxDB to a file, and import it in Marple. Today, they access their measurements directly in the Marple interface. Marple reads straight from InfluxDB, eliminating the need to store the data twice.

Marple expands your visualisation toolbox with things engineers need:

• Show GPS data in a map plot
• Create multi-signal scatter plots, coloured based on another signal
• Analyse resonance frequencies with FFT plots
• Apply custom calculations such as low pass, derivative, outliers, …

All these things are made with interactivity in mind, so Marple and InfluxDB will speed up the queries for you behind the scenes.

Marple also allows you to enrich datasets with metadata. One InfluxDB bucket can contain billions of sensor data points from different test and simulations. Engineers from Verhaert are using Marple to get their database more organised. They assign metadata such as a test number, who was responsible, and what equipment was used. In some cases they even attach a picture of the setup, or a pdf with a report.

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If you want to see it for yourself, give it a try with a free account. Connecting your InfluxDB database should take you less than 10 minutes. Watch the video below, or read our getting started docs.