Case Studies

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

VARTA AG saves over 400 hours a month by empowering teams to access and query MongoDB data without relying on developers.

Kanso Software uses Studio 3T

Kanso Software boosts MongoDB efficiency by 90%, saves $36K per developer

Kanso Software saved $2,800 saved per month per developer – a $36,000 annual saving. They also increased dev efficiency by 90% – 3 hours per day, per developer.

Employee recognition by Terryberry

Terryberry saves an estimated $185K per year with Studio 3T

Within eighteen months all their existing fifty or so customer sites had been migrated over to MongoDB. Their growing ability to develop faster and deliver new features and benefits to customers meant growth was accelerating.

Financial data intelligence platform

Financial data intelligence platform saves time and reduces operating costs

For programmers Studio 3T speeds up the writing of long and convoluted queries, ironing out typos and human error. For the non-programmers it works intuitively and requires no coding.

Wakefield Inspection Services (WIS)

Wakefield Inspection Services easily and successfully migrates SQL to MongoDB

The business of cotton inspection and data tracking is a bewitching blend of the traditional up to 400 years traditional – and the super modern – pulling data from APIs being rewritten hourly. And the range of data that is being gathered is highly specific to the nature of the cotton plant itself.

SBIA sports betting

SBIA uses Studio 3T to take optimized aggregation to the next level

Studio 3T allows SBIA to tune their platform on the fly by letting them create new optimized aggregations, generate new Python code, and reload it live into the platform infrastructure.

SEGA

Studio 3T helps give SEGA the confidence to check that things are running as they are

In order to ensure that SEGA can scale to millions of lifetime users, avoid latency in performance, and supply a satisfying mobile gaming experience, they have begun using MongoDB as the backend, with servers written in NodeJS.

Building a queryable image bank for tracking marine health

Tracking changes in phytoplankton and zooplankton populations and communities provides valuable insight into the impacts of ongoing environmental pressures and the effectiveness of conservation and management efforts.