MongoDB is a popular open-source, document-oriented NoSQL database. Instead of storing data in tables like traditional relational databases, MongoDB stores structured data in JSON-like documents.

• Document-oriented - stores data in flexible, JSON-like documents instead of rows and columns
• Scalability - easy to scale horizontally with automatic sharding
• High performance - performs well with large datasets and heavy workloads
• High availability - supports replication and failover for high availability
• Flexible data model - dynamic schemas allow you to store different data in the same collection
• Indexing - indexes support faster queries and can include keys from embedded documents and arrays

The main components of MongoDB are:

• mongod - The MongoDB daemon that does the core data storage
• mongos - The query router that provides sharding
• Documents - Data records composed of field-value pairs
• Collections - Groupings of MongoDB documents
• Databases - Container for collections

• JSON-like documents contain field-value pairs
• Collections contain sets of documents
• Databases contain collections
• Uses BSON format to store documents (binary JSON)

• show data bases: show dbs
  • if you have a data base which is empty the show dbs command won't show the empty data base.
• switch to data base : use 'data base name'
• create data base : use 'name of the data base you want'
• create collection : db.createCollection("name")
• drop data base : db.dropDatabase()

• to insert a document : db.students.insertOne({name:"gholi", age:30, gpa:2.5})
• to return all documents in a collection : db.students.find()
• add multiple documents : db.students.insertMany([{name: "gholi", age: 38, gpa: 2.5}, {name: "gholam", age: 39, gpa: 3.5}, {name: "ghodrat", age: 40, gpa: 4.5}])

db.students.insertOne({
name:"gholi", //string
age:32, //integer
gpa:2.8, // double
fullTime: false, // boolean
registerDate: new Date(), // date
gradDate: null, // null
courses: ["chemistry", "physics", "calculus"], // array
addres: {street:"fake street",
		 city: "gholi abad",
		 zip: 12345}}) // nested documents
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• find any students named "gholi" : db.students.find({name:"gholi"})
  • you can add multiple filters : db.students.find({name:"gholi", gpa: 4.0})
• find every students but only show their name : db.students.find({}, {name:true})
  • disable id's : db.students.find({}, {_id:false, name:true})

• update one data : db.students.updateOne(filter, update)
• adding / changing a full time field : db.students.updateOne({name:"gholi"}, {$set:{fulltime:true}})
• remove field : db.students.updateOne({name:"gholi"}, {$unset:{fulltime:""}})
  • to remove a field just set to an empty string.
• update multiple : db.students.updateMany({name:"gholi"}, {$set:{fulltime:false}})
• remove multiple : db.students.updateMany({name:"gholi"}, {$set:{fulltime:false}})
• check if a field exist : db.students.updateMany({fullTime:{$exists:false}}, {$set:{fulltime:true}})

• delete one document : db.students.deleteOne({name:"gholi"})
• delete multiple document : db.students.deleteMany({name:"gholi"})
• delete if something doesn't exist : db.students.deleteMany({registerDate:{$exist:false}})

• the not(!) operator : $ne
  • example to find anyone but "gholi" : db.students.find({name:{$ne:"gholi"}})
• less than(<) operator : $lt
  • example to find people under 20 yo : db.students.find({age:{$lt:20}})
  • less than or equal : $lte
  • greater than : $gt
  • greater than or equal : $gte
• multiple operators : db.students.find({gpa:{$lt:4, $gte:3}})
• in operator : $in
  • example : db.students.find({age:{$in:["gholi", "ghodrat"]}})
• not in operator : $nin
  • example : db.students.find({age:{$nin:["gholi", "ghodrat"]}})

• and operator : $and
  • example : db.students.find({$and: [{fullTime: true}, {age:{$lte:22}}]})
• or operator : $or
  • example : db.students.find({$or: [{fullTime: true}, {age:{$lte:22}}]})
• nor operator : $nor
  • example : db.students.find({$nor: [{fullTime: true}, {age:{$lte:22}}]})
• not operator : $not
  • db.students.find({age:{$not:{$gte:30}}})

1. Indexes help MongoDB perform queries faster by sorting documents in the collection on a specific field or set of fields.
2. Indexes are created on one or more fields of a collection to improve the speed of find(), sort() and grouping operations.

• how to make alphabetical index for a field : db.students.createIndex({name: 1})
• get Indexes : db.students.getIndex()
• drop Index by using name of the Index : db.students.getIndex("name_1")

• create Collections : db.createCollection("teachers")
• set max size to a collection : db.createCollection("teachers", {capped:true, size:10000000, max:100}) this means the size is at most 10 megabytes and maximum number of documents can be 100.
• you can set indexes to false so the insert and other operations are faster : db.createCollection("teachers", {capped:true, size:10000000, max:100}, {autoIndexId: false})