VARTA AG empowers users to self-serve MongoDB data and saves 400+ dev hours a month

Posted on: 28/08/2025 (last updated: 10/09/2025) • Luke Jovetic •

About VARTA AG

VARTA AG produces and markets a comprehensive battery portfolio ranging from microbatteries, household batteries, and energy storage systems to customized battery solutions for a wide range of applications. Through intensive research and development, VARTA AG sets global standards in many areas of lithium-ion technology and microbatteries, making it the recognised innovation leader in the key growth markets for lithium-ion technology and primary hearing aid batteries. The VARTA AG Group currently employs around 4,000 people. With five production and manufacturing facilities in Europe and Asia as well as distribution hubs in Asia, Europe and the USA, VARTA AG’s operating subsidiaries are currently active in over 100 countries worldwide.

How VARTA AG uses MongoDB data

VARTA AG’s in-house team uses MongoDB to manage its production data. This includes a serialization number for each battery, where it was made, under what conditions, using which materials, and on which machines. Multiple departments need access to this data, including quality assurance, R&D, and process development. 

What challenges did VARTA AG need to overcome?

When VARTA AG first deployed MongoDB, it used Compass and native MongoDB tools. The team soon realized these were not enough to meet their needs, as non-technical users were unable to directly access data. Instead, they submitted daily requests to developers. This created massive inefficiencies and delays, diverting developers from more valuable work and causing delays for other departments.

Challenge 1: Enabling self-service data access across departments

VARTA AG’s in-house software team faced a growing bottleneck of data access requests from other departments, including quality assurance, R&D, and process development. As non-technical users had no way to query MongoDB directly, every request, no matter how simple, had to go through the developers. They needed to manually write MongoDB queries, export the data, and send it back. Even at the beginning (with request limits in place) the development team received around 14 data access requests per week, and demand soon grew. As each one took one to two hours to deal with, the team was soon spending an unsustainable 400 hours per month on this task alone. 

VARTA AG needed a solution that would empower non-technical users to access data, without learning MongoDB’s query language or waiting for developer support.

Solution: A feature that allows non-technical users to query MongoDB data 

Studio 3T’s intuitive Visual Query Builder empowers around 50 non-technical users to easily query MongoDB data. With simple drag-and-drop functionality, there’s no need to know MongoDB’s query language or rely on the IT team. This has removed bottlenecks, saved over 400 hours of developer time per month and significantly increased access to insights across the business.

Challenge 2: Overcome complex querying and aggregation

MongoDB’s query language can be challenging to learn, especially when it’s used to build complex aggregation pipelines. For VARTA AG’s software development team, this complexity slowed down internal development and made it impossible for many users to access deeper insights without help. The team needed a way to build, visualize, and debug multi-stage aggregations and queries to speed up development and empower others to extract meaningful insights independently.

Solution: Simplify querying and aggregation for all users 

Studio 3T’s Query Builder and Aggregation Editor allow non-technical users to view data in a way that has never previously been possible and reduces reliance on experts. Even for developers, these features dramatically reduce the time and complexity of writing MongoDB queries and aggregations. VARTA AG developers can build complex aggregations in a fraction of the time it previously took, which in turn gives them more time to focus on critical tasks. They also benefit from improved accuracy and visibility into results at every pipeline stage.

Challenge 3: Reliably managing large datasets

VARTA AG needed a tool that could reliably handle large datasets. Each of their lithium-ion batteries generates complex serialized data across 10 to 15 production steps, and some exports involve hundreds of thousands or even millions of documents. VARTA AG initially used other tools, but quickly discovered that it couldn’t handle the scale or demands of their real-world workloads. Day-to-day tasks, like exporting tens of thousands of documents, would cause the product to crash. These limitations were not only slowing down progress, they were threatening to halt it entirely. Without an alternative, the team would have had to build an internal data export tool from scratch.

Solution: Make exports easy to manage 

Studio 3T tools like Migration to SQL and Export Wizard allow VARTA AG to move millions of documents at a time. This operational stability gives developers confidence in exporting massive datasets and removes the need for its team to create an internal data export tool. 

Challenge 4: Comparing environments and improving performance

VARTA AG’s development process includes changes to data processing pipelines. The company needed a way to test and validate results across staging and production environments. Previously, this was a time-consuming and error-prone process as it involved comparing data between clusters, manually exporting datasets, writing custom scripts, and conducting side-by-side reviews. They also needed to evaluate performance and optimize indexing in MongoDB. 

Solution: Less guesswork, more reliable results

VARTA AG uses Studio 3T’s Data Compare feature to compare new processing pipelines in staging versus production. The Index Manager also helps the team tune performance by optimizing queries and indexes. This gives it increased confidence in deploying software changes, reduces the likelihood of production issues and improves MongoDB performance through better indexing. 

Challenge 5: Getting internal buy-in and scaling usage

The VARTA AG team wanted buy-in for a more robust tool and needed to show how its capabilities could resolve or ease their current challenges. After evaluating a range of tools, it found Studio 3T was the best fit for its needs. The team needed to make a compelling case to introduce Studio 3T to the wider business. While developers would likely be aware of many of the benefits of the tool, there was a need to highlight the need for its use across departments. An initial trial and demonstration of features the company’s senior leadership could easily understand was a good place to start. 

Solution: Studio 3T trial to showcase the potential impact

Studio 3T was initially tested by two users and quickly proved itself during a free trial period. When pitching the tool to senior leadership, the team highlighted its SQL interface. This was more familiar to non-developers and helped secure buy-in. Once users realized that Studio 3T’s Visual Query Builder was even easier than writing SQL, demand quickly increased. More than 50 users, across multiple departments, now use it to access data independently with little to no training.