What are the differences between MongoDB and SQL aggregation?

What are the differences between MongoDB and SQL aggregation?

MongoDB uses a document-based model, while SQL uses a table-based model. Aggregation in MongoDB is done using the aggregation pipeline, which allows for more flexible data manipulation. In SQL, aggregation is typically done using GROUP BY clauses.

Can you explain how the aggregation pipeline works in MongoDB?

Sure! The aggregation pipeline in MongoDB consists of multiple stages, each transforming the data as it passes through. Stages can include filtering, grouping, and sorting, allowing for complex data processing.

How does SQL handle aggregation differently?

In SQL, aggregation is often done using functions like COUNT, SUM, AVG, etc., combined with GROUP BY to summarize data. It’s more rigid compared to MongoDB's flexible pipeline.

Which one is better for large datasets?

It depends on the use case. MongoDB can handle large datasets with its horizontal scaling, while SQL databases are optimized for complex queries and transactions.