Collection commands provide operations for managing collections within your database.
collection list List all collections in the database with document counts.
jasonisnthappy < DATABAS E > collection list
Example jasonisnthappy mydb.db collection list
Output Collections (3): • users (1,234 documents) • orders (5,678 documents) • products (432 documents)
┌──────────┬───────────┐ │ Name │ Documents │ ├──────────┼───────────┤ │ users │ 1,234 │ │ orders │ 5,678 │ │ products │ 432 │ └──────────┴───────────┘
[ { "name" : "users" , "document_count" : 1234 }, { "name" : "orders" , "document_count" : 5678 }, { "name" : "products" , "document_count" : 432 } ]
collection create Create a new collection. Collections are created automatically on first insert, but explicit creation can be useful for setting up schemas or indexes beforehand.
jasonisnthappy < DATABAS E > collection create < NAM E >
Arguments
name - Name of the collection to create
Example Create users collection
Create orders collection
jasonisnthappy mydb.db collection create users
Output ✓ Collection 'users' created successfully
Collection names must be unique within a database. Creating a collection that already exists will return an error.
collection drop Permanently delete a collection and all its documents, indexes, and schemas.
jasonisnthappy < DATABAS E > collection drop < NAM E >
Arguments
name - Name of the collection to drop
Example jasonisnthappy mydb.db collection drop temp_data
Output ✓ Collection 'temp_data' dropped successfully Documents deleted: 1,234 Indexes removed: 3
This operation is irreversible. All documents in the collection will be permanently deleted.
collection info Display detailed information about a specific collection including document count, size, indexes, and schema.
jasonisnthappy < DATABAS E > collection info < NAM E >
Arguments
name - Name of the collection to inspect
Example jasonisnthappy mydb.db collection info users
Output Collection: users Statistics: Documents: 1,234 Size: 456 KB Average Document Size: 379 bytes Indexes: • email (unique) • created_at • age Schema: Validation: enabled Required fields: name, email Created: 2025-01-15 10:30:22 Modified: 2025-03-03 14:22:11
{ "name" : "users" , "document_count" : 1234 , "size_bytes" : 467968 , "average_doc_size" : 379 , "indexes" : [ { "field" : "email" , "unique" : true }, { "field" : "created_at" , "unique" : false }, { "field" : "age" , "unique" : false } ], "schema" : { "enabled" : true , "required" : [ "name" , "email" ] }, "created_at" : "2025-01-15T10:30:22Z" , "modified_at" : "2025-03-03T14:22:11Z" }
index list List all indexes for a collection.
jasonisnthappy < DATABAS E > index list < COLLECTIO N >
Arguments
collection - Name of the collection
Example jasonisnthappy mydb.db index list users
Output Indexes for collection 'users': • email (unique) • created_at • age • status
┌────────────┬────────┐ │ Field │ Unique │ ├────────────┼────────┤ │ email │ ✓ │ │ created_at │ │ │ age │ │ │ status │ │ └────────────┴────────┘
[ { "field" : "email" , "unique" : true }, { "field" : "created_at" , "unique" : false }, { "field" : "age" , "unique" : false }, { "field" : "status" , "unique" : false } ]
index create Create an index on a field to improve query performance.
jasonisnthappy < DATABAS E > index create < COLLECTIO N > < FIEL D > [--unique]
Arguments
collection - Name of the collectionfield - Field name to index (supports dot notation for nested fields)
Flags
--unique / -u - Make this a unique index (prevents duplicate values)
Examples Regular index
Unique index
Nested field index
jasonisnthappy mydb.db index create users email
Output ✓ Index created on field 'email' Collection: users Unique: true Documents indexed: 1,234 Duration: 45ms
Indexes dramatically improve query performance but use additional disk space. Create indexes for fields you frequently query.
index drop Remove an index from a collection.
jasonisnthappy < DATABAS E > index drop < COLLECTIO N > < NAM E >
Arguments
collection - Name of the collectionname - Name of the index (field name)
Example jasonisnthappy mydb.db index drop users email
Output ✓ Index 'email' dropped from collection 'users'
schema set Set or update the JSON Schema validation for a collection.
jasonisnthappy < DATABAS E > schema set < COLLECTIO N > < SCHEM A >
Arguments
collection - Name of the collectionschema - JSON Schema definition (as JSON string)
Example jasonisnthappy mydb.db schema set users '{ "type": "object", "required": ["name", "email"], "properties": { "name": {"type": "string"}, "email": {"type": "string", "format": "email"}, "age": {"type": "number", "minimum": 0} } }'
Output ✓ Schema set for collection 'users' Required fields: name, email Optional fields: age
Setting a schema validates future inserts and updates but doesn’t automatically validate existing documents. Use schema validate to check existing data.
schema get Retrieve the current schema for a collection.
jasonisnthappy < DATABAS E > schema get < COLLECTIO N >
Arguments
collection - Name of the collection
Example jasonisnthappy mydb.db schema get users
Output { "type" : "object" , "required" : [ "name" , "email" ], "properties" : { "name" : { "type" : "string" }, "email" : { "type" : "string" , "format" : "email" }, "age" : { "type" : "number" , "minimum" : 0 } } }
schema validate Validate all existing documents in a collection against the current schema.
jasonisnthappy < DATABAS E > schema validate < COLLECTIO N >
Arguments
collection - Name of the collection
Example jasonisnthappy mydb.db schema validate users
Output Validating collection 'users'... ✓ Valid documents: 1,230 ✗ Invalid documents: 4 Invalid documents: ID 567: Missing required field 'email' ID 890: Field 'age' must be >= 0 ID 1024: Invalid email format ID 1234: Field 'name' must be string
Run schema validation after setting a new schema to identify documents that need updating.
Document commands Insert, query, and modify documents
Database commands Database-level operations