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Mestrelab Research
Mestrelab Research
Mestrelab Research is a scientific software company with nearly two decades of expertise, specializing in providing advanced solutions in the field of analytical chemistry. As a fast-growing company, we have doubled in size over the past five years, now boasting over 90 employees spread across headquarters in Santiago de Compostela (Spain), as well as offices in Europe, Asia, and the USA.
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Mgears 2.7 Introduces a new NoSQL DB Connector

Th, 3.7.2025
| Original article from: Mestrelab Research
The new Mnova 16 release brings enhanced scientific data handling through the NoSQL DB Connector included in Mgears 2.7, offering flexible and scalable result management.
<p><strong>Mestrelab Research:</strong> Mgears 2.7 Introduces a new NoSQL DB Connector</p>

Mestrelab Research: Mgears 2.7 Introduces a new NoSQL DB Connector

With the release of Mnova 16, a new and powerful way to handle results from scientific data analysis is now available by using the NoSQL DB Connector, included in Mgears 2.7.

This new connector enables direct integration with NoSQL databases such as MongoDB and Amazon DocumentDB, allowing for flexible, scalable, and searchable storage of Mgears results – perfect for high-throughput environments and complex workflows.

A newly published Application Note explores:

  • When and why connecting Mgears to a NoSQL DB is beneficial
  • How to send results from Mgears to a NoSQL DB
  • How to build filtered views to show selected sample data
  • How to create simple views for use in BI tools like Spotfire
  • How data stored in NoSQL DB can be connected to AI frameworks like TensorFlow for building predictive models

These capabilities are illustrated with real examples using datasets from LCMS system suitability testing and reaction optimization analysis, demonstrating how this connector offers the capability to handle analytical data in a more dynamic way resulting in faster data-driven decision-making.

The connector works with Mgears’ native JSON outputs and avoids the need for predefined schemas – making it especially suitable for workflows that evolve over time.

Read the full Application Note.

Mestrelab Research
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