Querying Arrays: $all, $size, and Element Match
Learners will filter documents by array contents using $all for multi-element matching and $size for length checks.
Querying Arrays: $all, $size, and Element Match is a free MongoDB Academy lesson on CoddyKit — lesson 1 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the MongoDB Academy learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
Arrays as First-Class Citizens
In MongoDB, arrays are a native BSON type that can be stored directly in a document field. Unlike relational databases where arrays require a separate junction table, MongoDB lets you embed arrays of any type—scalars, sub-documents, or mixed—directly in the document. This makes arrays one of the most useful features but also one of the most nuanced to query correctly.
// Documents with array fields
db.products.insertMany([
{ name: 'Laptop', tags: ['electronics', 'computers', 'portable'] },
{ name: 'Mouse', tags: ['electronics', 'peripherals'] },
{ name: 'Book', tags: ['education', 'reading'] }
]);Simple Array Equality Queries
A simple equality filter on an array field checks whether the array contains the specified value as an element. You don't need a special operator—just write the filter as if the field were a scalar. MongoDB will match any document where the array contains that exact value anywhere in it.
// Find products tagged 'electronics'
// MongoDB checks if 'electronics' is an element of the tags array
db.products.find({ tags: 'electronics' });
// Returns Laptop and Mouse (both have 'electronics' in tags)
// This also works on arrays of numbers
db.scores.find({ values: 95 });
// Matches { values: [80, 95, 72] }The $all Operator
The $all operator matches documents where the array contains all of the specified values, in any order. Unlike a plain equality check (which matches a single element), $all enforces that every specified element is present. Think of it as multiple AND conditions on array membership.
// Find products tagged BOTH 'electronics' AND 'portable'
db.products.find({
tags: { $all: ['electronics', 'portable'] }
});
// Returns Laptop (has both tags)
// Does NOT return Mouse (missing 'portable')
// Order of values in $all does not matter
db.products.find({
tags: { $all: ['portable', 'electronics'] } // same result
});The $size Operator
The $size operator matches documents where the array field has exactly the specified number of elements. It accepts a literal integer—you cannot use range comparisons like $gt with $size directly. For range-based length checks, use a field that stores the array length alongside the array, or use an aggregation with $where.
// Find products with exactly 3 tags
db.products.find({ tags: { $size: 3 } });
// Returns Laptop (tags has 3 elements)
// $size does NOT support ranges:
// db.products.find({ tags: { $size: { $gt: 2 } } }); // INVALID
// Workaround: store the count as a field
db.products.updateMany({}, [{ $set: { tagCount: { $size: '$tags' } } }]);
db.products.find({ tagCount: { $gt: 2 } }); // range check on stored countMatching by Array Index
You can query by a specific position in an array using dot notation with an index number. For example, { 'scores.0': 100 } matches documents where the first element of the scores array is 100. This is useful when array order is meaningful, such as a ranked list or time-ordered sequence.
// Documents: { name: 'Alice', scores: [100, 85, 92] }
// { name: 'Bob', scores: [75, 88, 91] }
// Find documents where the FIRST score is 100
db.results.find({ 'scores.0': 100 });
// Returns Alice
// Find where SECOND element is greater than 85
db.results.find({ 'scores.1': { $gt: 85 } });
// Returns Bob (scores[1] = 88 > 85) and Alice (85 is NOT > 85)The Spread Field Problem
A subtle gotcha: when you filter an array of sub-documents with multiple conditions on different fields, MongoDB applies each condition independently across all array elements—not to a single element. This is called the spread field problem. For example, { 'scores.value': { $gt: 90 }, 'scores.grade': 'A' } matches if any element has value > 90 AND any element has grade 'A'—they don't have to be the same element.
// Documents:
// { scores: [{ value: 95, grade: 'A' }, { value: 60, grade: 'D' }] }
// { scores: [{ value: 92, grade: 'B' }, { value: 72, grade: 'C' }] }
// This filter has SPREAD FIELD issue:
// Matches doc1 (value 95>90 is in scores[0], grade 'A' is in scores[0] - fine here)
// Also matches doc2 if value 92>90 from one element + some 'B'... but what if:
// { scores: [{ value: 91, grade: 'B' }, { value: 62, grade: 'A' }] }
// This would ALSO match! 91 > 90 from element[0] + grade 'A' from element[1]$elemMatch for Multi-Condition Array Queries
The $elemMatch query operator solves the spread field problem by requiring all conditions to be satisfied by the same single array element. Wrap your conditions in { $elemMatch: { condition1, condition2 } } and MongoDB will only return documents where at least one array element satisfies all the specified conditions simultaneously.
// Find documents where a SINGLE scores element has value > 90 AND grade 'A'
db.results.find({
scores: {
$elemMatch: {
value: { $gt: 90 },
grade: 'A'
}
}
});
// Only matches if one element has BOTH value > 90 AND grade 'A'$elemMatch for Scalar Arrays
$elemMatch can also be applied to arrays of scalar values (strings, numbers) when you need to apply multiple operators to the same element. For example, finding elements that are both greater than 10 and less than 20—without $elemMatch, these conditions could be satisfied by two different elements.
// Find docs where a SINGLE element is between 10 and 20
db.measurements.find({
values: { $elemMatch: { $gt: 10, $lt: 20 } }
});
// { values: [5, 15, 25] } - matches (15 satisfies both)
// { values: [5, 30] } - does NOT match
// Without $elemMatch (wrong - tests across elements):
db.measurements.find({ values: { $gt: 10, $lt: 20 } });
// { values: [5, 30] } WOULD match! (5 < 20, 30 > 10, different elements)Combining $all and $elemMatch
You can use $all with $elemMatch expressions inside it to require multiple complex conditions across multiple distinct array elements. Each $elemMatch inside $all must be satisfied by a different element. This pattern is rarely needed but is available for complex multi-condition, multi-element requirements.
// Find docs where:
// - one element satisfies { value: { $gt: 90 }, grade: 'A' }
// - AND another element satisfies { value: { $lt: 70 }, grade: 'D' }
db.results.find({
scores: {
$all: [
{ $elemMatch: { value: { $gt: 90 }, grade: 'A' } },
{ $elemMatch: { value: { $lt: 70 }, grade: 'D' } }
]
}
});Arrays and Index Behaviour
An index on an array field automatically becomes a multikey index in MongoDB, with one index entry per array element. This means queries like { tags: 'electronics' } and { tags: { $all: ['electronics', 'portable'] } } both benefit from the index. However, a compound index cannot have multikey on more than one array field per document—attempting to do so throws an error.
// Index on tags field becomes multikey automatically
db.products.createIndex({ tags: 1 });
// These queries all use the multikey index efficiently:
db.products.find({ tags: 'electronics' });
db.products.find({ tags: { $all: ['electronics', 'portable'] } });
db.products.find({ tags: { $size: 3 } });
// Note: $size cannot use the index for size filtering
// (it still needs to check document-level array length)Using explain() With Array Queries
Array queries with $all and $elemMatch can sometimes surprise you with their index usage. Always verify with explain('executionStats'). A $size filter will show IXSCAN on the multikey index but still examine all index entries (since size is not stored in the index). An $elemMatch on indexed fields will use IXSCAN on the matching element conditions.
// Check how array queries use indexes
db.products.find({
tags: { $all: ['electronics', 'portable'] }
}).explain('executionStats');
// Look for:
// stage: 'IXSCAN' - index is being used
// totalKeysExamined vs nReturned ratioQuick Check
Test your understanding of array query operators in MongoDB.
Lesson Recap
In this lesson you learned: $all requires an array to contain all specified values, $size matches arrays with an exact number of elements, and $elemMatch ensures multiple conditions apply to the same single array element, solving the spread field problem. Next up we dive deeper into $elemMatch for matching array sub-documents.
Frequently asked questions
Is the “Querying Arrays: $all, $size, and Element Match” lesson free?
Yes — the full text of “Querying Arrays: $all, $size, and Element Match” is free to read here on the web, and the MongoDB Academy course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the MongoDB Academy course, upgrade to CoddyKit PRO.
What will I learn in “Querying Arrays: $all, $size, and Element Match”?
Learners will filter documents by array contents using $all for multi-element matching and $size for length checks. You practise MongoDB Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start MongoDB Academy?
No prior experience is required. MongoDB Academy on CoddyKit is structured for beginners through advanced learners; this is — lesson 1 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Querying Arrays: $all, $size, and Element Match” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this MongoDB Academy lesson?
Yes. Every MongoDB Academy lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Querying Arrays: $all, $size, and Element Match
- $elemMatch: Matching Array Sub-Documents
- Updating Arrays: $push, $pull, $pop, $addToSet
- Positional and Filtered Positional Updates