例子:
> db.stuff.save({"foo":"bar"});
> db.stuff.find({"foo":"bar"}).count();
1
> db.stuff.find({"foo":"BAR"}).count();
0
当前回答
最好的方法是在你选择的语言中，当为你的对象创建模型包装器时，让你的save()方法遍历一组你将搜索的字段，这些字段也被索引了;这组字段应该有对应的小写字母，然后用于搜索。
每次再次保存对象时，都会检查小写属性并更新主属性的任何更改。这将使您可以有效地搜索，但隐藏了每次更新lc字段所需的额外工作。
小写字段可以是一个键值对象存储，或者只是字段名加上前缀lc_。我使用第二种方法来简化查询(深度对象查询有时会令人困惑)。
注意:您希望索引lc_字段，而不是它们所基于的主字段。
其他回答
从MongoDB 3.4开始，执行快速不区分大小写搜索的推荐方法是使用不区分大小写索引。
我亲自给其中一位创始人发了邮件，请他把这个工作做好，他做到了!自2009年以来，JIRA上就有这个问题，许多人都要求提供这个功能。下面是它的工作原理:
通过指定强度为1或2的排序规则，可以创建不区分大小写的索引。你可以像这样创建一个不区分大小写的索引:
db.cities.createIndex(
{ city: 1 },
{
collation: {
locale: 'en',
strength: 2
}
}
);
你也可以在创建集合时指定一个默认的排序规则:
db.createCollection('cities', { collation: { locale: 'en', strength: 2 } } );
在这两种情况下，为了使用不区分大小写的索引，你需要在find操作中指定与创建索引或集合时使用的相同的排序规则:
db.cities.find(
{ city: 'new york' }
).collation(
{ locale: 'en', strength: 2 }
);
这将返回"New York"， "New York"， "New York"等。
其他的笔记
The answers suggesting to use full-text search are wrong in this case (and potentially dangerous). The question was about making a case-insensitive query, e.g. username: 'bill' matching BILL or Bill, not a full-text search query, which would also match stemmed words of bill, such as Bills, billed etc. The answers suggesting to use regular expressions are slow, because even with indexes, the documentation states: "Case insensitive regular expression queries generally cannot use indexes effectively. The $regex implementation is not collation-aware and is unable to utilize case-insensitive indexes." $regex answers also run the risk of user input injection.
你可以使用不区分大小写的索引:
下面的示例创建一个没有默认排序规则的集合，然后在名称字段上添加一个索引，排序规则不区分大小写。Unicode国际组件
/* strength: CollationStrength.Secondary
* Secondary level of comparison. Collation performs comparisons up to secondary * differences, such as diacritics. That is, collation performs comparisons of
* base characters (primary differences) and diacritics (secondary differences). * Differences between base characters takes precedence over secondary
* differences.
*/
db.users.createIndex( { name: 1 }, collation: { locale: 'tr', strength: 2 } } )
要使用索引，查询必须指定相同的排序规则。
db.users.insert( [ { name: "Oğuz" },
{ name: "oğuz" },
{ name: "OĞUZ" } ] )
// does not use index, finds one result
db.users.find( { name: "oğuz" } )
// uses the index, finds three results
db.users.find( { name: "oğuz" } ).collation( { locale: 'tr', strength: 2 } )
// does not use the index, finds three results (different strength)
db.users.find( { name: "oğuz" } ).collation( { locale: 'tr', strength: 1 } )
或者你可以创建一个默认排序规则的集合:
db.createCollection("users", { collation: { locale: 'tr', strength: 2 } } )
db.users.createIndex( { name : 1 } ) // inherits the default collation
如果你正在使用MongoDB Compass:
转到筛选器类型的集合-> {Fieldname: /string/i}
对于使用Mongoose的Node.js:
模型。find({FieldName: {$regex: "stringToSearch"， $options: "i"}})
db.company_profile.find({ "companyName" : { "$regex" : "Nilesh" , "$options" : "i"}});
博士TL;
正确的方法做到这一点在mongo
不使用RegExp
使用mongodb的内置索引，搜索
第一步:
db.articles.insert(
[
{ _id: 1, subject: "coffee", author: "xyz", views: 50 },
{ _id: 2, subject: "Coffee Shopping", author: "efg", views: 5 },
{ _id: 3, subject: "Baking a cake", author: "abc", views: 90 },
{ _id: 4, subject: "baking", author: "xyz", views: 100 },
{ _id: 5, subject: "Café Con Leche", author: "abc", views: 200 },
{ _id: 6, subject: "Сырники", author: "jkl", views: 80 },
{ _id: 7, subject: "coffee and cream", author: "efg", views: 10 },
{ _id: 8, subject: "Cafe con Leche", author: "xyz", views: 10 }
]
)
第二步:
需要在你想要搜索的任何TEXT字段上创建索引，没有索引查询将会非常慢
db.articles.createIndex( { subject: "text" } )
第三步:
db.articles.find( { $text: { $search: "coffee",$caseSensitive :true } } ) //FOR SENSITIVITY
db.articles.find( { $text: { $search: "coffee",$caseSensitive :false } } ) //FOR INSENSITIVITY
