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We use the Aggregation Editor to debug our stages. To check the pipeline and make sure that we’re getting the correct results that we’re looking for. It then shows us the results visually in a nice way, we don’t have to do things manually, stats and all that.

Abdelraham Hafez
Backend Lead Engineer at Speero

MongoDB Tool in Action: Aggregation Editor

MongoDB aggregation in Studio 3T is powerful and precise. Whether it’s to fine-tune results or performance, you get granular control at every stage while keeping the full view of your data – never just sample sets.

From data validation to producing fast and rich data streams for analytics and visualization tools, aggregations bring your project to the next level.

Debugging

The development team at Speero, a Riyadh based automotive parts marketplace, has benefited greatly from using Studio 3T’s Aggregation Editor in their workflow.

Ameen Mahfouz, one of its founders, shared some of their main usages for the Aggregation Editor:

We debug the data quality in our collections, so we would know if any record or any document that is not consistent with the other document. For example, if you see some variation in the data type of some fields or some references are missing. We use it to debug especially when some weird bug arises.

Reporting and analytics

The Aggregation Editor can also transform your data by including parameters and elements across various collections. This is particularly useful for preparing data for BI and graphic visualization tools. An example of another company using aggregations to their full potential is SMT, the leading company in data integration technology and broadcast systems.

SMT makes several MongoDB applications for NASCAR, both for public broadcast and internal use.

NASCAR PitStop ReportPit stop tracking and reporting through SMT’s application for NASCAR, racing teams, and OEMs

Augusto Cardoso, Lead Engineer at SMT, explained how SMT’s pit-stop tracking app is actually used by Original Equipment Manufacturers (OEMs) to grant bonuses after each race to the best performing teams. The app’s calculations are updated in real time by a powerful MongoDB aggregation.

I don’t know if you can appreciate how fast this was. This aggregation there is 28 stages, I did the whole thing in Studio 3T.

SMT is able to track car positions (up to a 2 cm precision) and the duration of their pit-stops. On staged races like NASCAR’s, not only the timing of when to do a pit stop, but also how long it takes, are essential for teams and the OEMs.

Projects have defining breakthrough moments, which start with discovering the full potential of the tools and elements within your reach. 3T’s Aggregation Editor have provided this breakthrough for many developers, engineers, and administrators working with MongoDB.

Try Aggregation Editor for free today.