What is a characteristic of the aggregation operation in MongoDB?

The aggregation operation in MongoDB is designed primarily for summarizing and analyzing data. This capability allows users to transform and combine data from multiple documents and collections within a database and produce aggregated results such as counts, sums, averages, and a variety of statistical data.

Aggregation pipelines enable you to process data records and return computed results. This is achieved through various stages where documents can be filtered, sorted, reshaped, and grouped. For example, you can group documents by specific fields and calculate totals or averages, which can be incredibly useful for reporting and analytics.

In contrast, the other options fail to capture the full scope of what aggregation can do. The operation does not solely retrieve data or modify existing documents, as its primary function is aggregation. Additionally, while it can run efficiently using indexes to enhance performance, it is not limited to only running on indexes but can operate on regular collections as well. Thus, the characteristic that best defines the aggregation operation is its ability to summarize and analyze data effectively.