SQL vs NoSQL
SQL databases keep data in strict tables of rows and columns, while NoSQL databases like MongoDB use more flexible models.
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SQL vs NoSQL
Relational databases require a schema up front, use joins across normalized tables and speak SQL. MongoDB keeps related data together in one document, allows fields to vary, and uses a JSON query language.
Neither is better in general: choose by data shape, consistency needs and team skills.
Note:
A SQL row is roughly a MongoDB document, and a table is roughly a collection.
Example: SQL vs NoSQL
// SQL: SELECT name FROM users WHERE age > 30 ORDER BY name;
// Mongo: the same question as a query document
test> db.users.insertMany([{ _id: 1, name: "Cy", age: 41 }, { _id: 2, name: "Ada", age: 36 }, { _id: 3, name: "Bob", age: 25 }])
{ acknowledged: true, insertedIds: { '0': 1, '1': 2, '2': 3 } }
test> db.users.find({ age: { $gt: 30 } }, { name: 1, _id: 0 }).sort({ name: 1 })
[ { name: 'Ada' }, { name: 'Cy' } ]⚠️ Run this in your own terminal or Node.js environment.
Related Topics
Common Mistakes
- Assuming NoSQL means no transactions
- Assuming SQL cannot scale
- Copying a relational schema into MongoDB unchanged
Chapter Summary
- SQL uses tables, rows and joins
- MongoDB uses collections and documents
- MongoDB documents can vary in shape
- Choose by data and access patterns
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