Problem Statement
Explain the trade-offs between embedding documents versus referencing in MongoDB. When should you use each approach?
Explanation
Embedding and referencing are two fundamental approaches to modeling relationships in MongoDB, each with distinct advantages and trade-offs. The choice between them significantly impacts performance, data integrity, and application complexity.
Embedding stores related data within the same document. For example, storing a user's address directly inside the user document. Advantages include better read performance because all data is retrieved in a single query, atomicity where updates to embedded data are atomic, and locality where related data is stored together on disk.
Disadvantages of embedding include document size limits because documents cannot exceed 16 MB, data duplication when the same embedded data needs to appear in multiple parent documents, and unbounded growth problems when arrays can grow indefinitely. Embedding also makes it harder to query embedded data independently.
Referencing stores related data in separate documents and uses references like foreign keys to link them. For example, storing user ID in order documents to reference the user collection. Advantages include no duplication because shared data exists once, ability to query referenced data independently, and no size limits on the relationship.
Disadvantages of referencing include requiring multiple queries or dollar lookup to retrieve related data, no atomic updates across documents outside transactions, and increased complexity in application code to manage relationships.
Use embedding when you have one-to-one relationships, one-to-few relationships with a small bounded number of embedded documents, data that is always accessed together, data that rarely changes, or when atomic updates to related data are critical. For example, embed user addresses, order line items, or blog post comments.
Use referencing when you have one-to-many relationships with unbounded growth, many-to-many relationships, data that is frequently accessed independently, data that changes frequently and needs to be shared, or when document size approaches limits. For example, reference users from orders, products from categories, or students from courses.
In practice, hybrid models are common. You might embed frequently accessed fields for performance while referencing complete related documents. For example, embed author name and ID in blog posts for display, but reference the full author document for profile pages.