MongoDB

Overview

MongoDB is a document database that stores JSON-like (BSON) documents with flexible schemas, nested objects, and arrays. It provides a rich query language, aggregation pipelines for data transformation, multiple index types (text, TTL, wildcard, geospatial), ACID transactions, and horizontal scaling via sharding. MongoDB Atlas adds managed cloud hosting with full-text search ($search) and vector search ($vectorSearch); those two stages are Atlas features and are not part of a plain mongod.

Instructions

When designing schemas, embed data that is read together and reference data that is shared across documents, optimizing for read patterns rather than normalization since MongoDB penalizes joins ($lookup).
When querying, use dot notation for nested fields, array operators ($in, $elemMatch, $all) for array queries, and projection to return only needed fields.
When transforming data, use aggregation pipelines with stages like $match, $group, $project, $lookup, and $unwind rather than pulling data to application code for processing.
When creating indexes, add indexes for every production query pattern, use explain("executionStats") to verify usage, and choose TTL indexes for auto-expiring data like sessions and logs.
When enforcing data integrity, use JSON Schema validation on collections (db.createCollection(name, { validator: { $jsonSchema: {...} } }); a violating insert fails with DocumentValidationFailure), and use multi-document transactions only when atomicity across documents is required. Transactions need a replica set or sharded cluster, not a standalone server. Since MongoDB 5.0 the implicit write concern is majority for most deployments, so you only set it explicitly to override a changed default.
When scaling, choose shard keys with high cardinality and even distribution, set up replica sets for high availability, and configure read preferences based on consistency requirements. A shard key can be changed later with reshardCollection (MongoDB 5.0+), which rewrites the collection in the background, so it is possible but expensive.
Store money as Decimal128 (NumberDecimal("89.90") in mongosh), not doubles.

mongosh "mongodb://localhost:27017/shop" --eval 'db.products.getIndexes()'