Marple resources

See how Marple supercharges your Grafana setup, streamlining time-series analysis when dashboards alone just aren’t enough.

Explore the strengths and trade-offs of the top five time-series databases for high-frequency telemetry data, and find the right fit for your growing data volumes.

Explore five strategic approaches to rein in the rising costs of time-series databases, without sacrificing performance or functionality.

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Discover why CSV files still hold appeal for storing time-series data, even with their size, metadata and sampling limitations.

Our software is featured in Renumics’ leading list of the best data analysis tools for test engineers 🙌

We have recently completed an investment round to support our growth into automotive and aerospace.

In 2024, we had many teams that made use of Marple for the data analysis of their telemetry data. And what an extraordinary year it was for “our Formula Student teams”. We've witnessed multiple records being smashed, showing these young engineers' incredible talent and dedication. And of course, we are very proud to be part of this story!

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Why should you shift to a data-centric approach, and how can it benefit your business?

Discover five features of Marple that help engineering teams get valuable insights from raw sensor data.

When does it make sense to build your own in-house data visualisation tool, or when is buying the preferred option?

Azure Time Series Insights (TSI) is officially discontinued, so now what?

Compare popular tools like Marple, Grafana, Metabase, Jupyter Notebook, Google Sheets, and Plotly Chart on ease of use, performance, and data management.

Learn how to automate your data‑analysis workflow using the Marple API.

Learn how to tune a PID controller, step by step, in this blogpost. From setting the right proportional, integral and derivative gains to achieving stable, optimal loop performance.

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In this blog post, we explain why Marple is so good and fast at drawing plots of large amounts of time series data.

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Discover how Lilium integrated Marple as an essential tool in their flight test department.

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Marple founder Nero measured his body weight every 15 minutes for a full day. How much dus it vary?

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In this blog post, we compare InfluxDB and TimescaleDB across data models, performance, data importing, hardware integration, stability and tooling to find the best fit for your team.

This article provides an in-depth analysis of energy usage in Belgium, including patterns in energy consumption and production, and an examination of the different types of energy sources being used. The article includes dynamic graphs and statistical analysis of the data.

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Learn how a solar racing team uses data to gain insights from their solar panels, batteries and race strategy.

Variable stars have captured the attention of astronomers and amateur stargazers alike for centuries. Discover the data behind these fascinating astronomical objects.

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.

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Hello there!

We've had a busy couple of months since our last blog post. In this post we want to give you an update on two elements: our second test period and our first summer interns. Let's go!

Discover how Tine Wildiers uses Marple to get the Agoria Solar Team ready for the international solar challenge.

We're joining the imec.istart accelerator programme! What does that mean for our growing business?

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Marple is now being tested by various pilot testers.

Marple haalt half miljoen euro op om ingenieurs razendsnel inzicht te geven in hun data.

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Marple has been selected for the Quick Wins subsidy of POM. What does this mean for our growing business?

Marple raises half a million euro to give engineers lightning-fast insight into their data

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FSTD gets to use Marple to get on top of their test data, gain valuable insights for the design process and hopefully win the races!

Why have we decided to move from a desktop solution to a server-based solution? We're happy to explain!

Welcome to our first blog post!

Strava's estimated power output has sparked quite some discussions within our team, so we decided to put it to the test.

We have visited the Formula Student Team Delft (FSTD) to see how they use Marple to improve their performance and hopefully win the races!