Recently in MongoDB Category

We are using MongoDB on our project, since mongo is document store, schema design is somewhat different, when you are using traditional RDBMS data stores, one thinks about tables and rows, while using a document database you have to think about the schema in a some what different way. Lets say, we want to save a customer object, when using a RDBMS we would come up with Customer, Address, Phone, Email. They are related to each other as shown below. When doing a document database, the schema design actually does not change much, the Customer document contains an array of Addresses, a one to many relationship. You will not need the FK columns or the Primary Key columns on the child tables, since the child rows are embedded in the parent object. The JSON object below shows how the data would look.

{
"_id" : ObjectId("4bd8ae97c47016442af4a580"),
"customerid" : 99999,
"name" : "Foo Sushi Inc",
"type" : "Good",
"since" : "12/12/2001",
"addresses" : [{
		"address" : "4821 Big Street",
		"city" : "Stone",			
		"state" : "IL",
		"country" : "USA"
	},
	{	"address" : "1248 Barlow Ln",
		"city" : "Hedgestone",			
		"country" : "UK"
	}		
],
"emails" : [ 
	{"email" : "foousa@sushi.com"},
	{"email" : "foouk@sushi.com"}
],
"phones" : [ 
	{"phone" : "773-7777-7777"},
	{"phone" : "020-6666-6666"}
]
}

So Instead of 1 Row for customer, 2 rows for address, phone and email each, you get one Customer document. If you want to query for customers in USA. Using RDBMS you would do

SELECT customer.name FROM customer, address 
WHERE customer.customerid = address.customerid 
AND address.country="USA"

The same query in mongo would look like

db.customers.find({"addresses.country":"USA"},{"name":true})

where customers is the collection in which we store our customers.

The current project I'm on is using MongoDB. MongoDB is a document based database, it stores JSON objects as BSON (Binary JSON objects). MongoDB provides a middle ground between the traditional RDBMS and the NOSql databases out there, it provides for indexes, dynamic queries, replication, map reduce and auto sharding, its open source and can be downloaded here, starting up mongodb is pretty easy.

./mongod --dbpath=/user/data/db

is all you need, where /user/data/db is the path where you want mongo to create its data files. There are many other options that you can use to customize the mongo instance. Each mongo instance has databases and each database has many collections, mapping back to oracle, mongo database is a oracle schema and mongo collection is a oracle table, The difference is, each collection can hold any type of object, basically every row can be different. An example connection to the database using java looks like this

   Mongo mongo = new Mongo("localhost");
   db = mongo.getDB("mydatabase");

If the "mydatabase" does not exist, it will be created. When you want to put objects in the database, you need to have a collection which holds the objects.

   users = db.getCollection("applicationusers");

if the "applicationusers" collection does not exist, it will be created, at this point you are ready to put objects into the collection.

    BasicDBObject userDocument = new BasicDBObject();
    userDocument.put("name", "jack");
    userDocument.put("type", "super");
    users.insert(userDocument);

You create a document by using the BasicDBObject and put attribute names and their values, in the above example "name" is the attribute and "jack" is the value, the users.insert takes the document and inserts it into the collection "users". At this point you have a JSON object put into the database. You can query for the object using the mongo query tool or the rest full api mongo provides using the flag --rest, when you start mongodb, visiting http://127.0.0.1:28017/mydatabase/users/ should give you

{
  "offset" : 0,
  "rows": [
    { "_id" : { "$oid" : "4bc9157e201f254d204226bf" }, "name" : "jack", "type" : "super" }
  ],
  "total_rows" : 1 ,
  "query" : {} ,
  "millis" : 0
}

Every object you insert, gets a auto generated id, more about update, delete and complex objects in next blog post.