MongoDB is an open-source NoSQL-Database developed by 10gen in C++.

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Open source, High performance, Document oriented
Albin John
S5 MCA
NO:04
NIELIT Calicut

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Need of MongoDB
Relational vs. NoSQL Comparison
 What is MongoDB?
MongoDB Key Features

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• To understand we need to look at
• BigData
• NoSQL

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• Massive volume of both structured and
unstructured data , which is difficult to process
using traditional database and software
techniques.

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• Approximately 90 percent of all the real-time
information being created today is unstructured data.
• Every day 2.5 quintillion (1018) bytes of data are being
generated.
• 90 percent of world's present day data has been
created in the two previous years alone.

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• High Volume – amount of data
– Facebook take 500 terabytes of new data every day
• High Variety – range of data types and sources
– geospatial data, audio and video etc..
• High Velocity – speed of data in and out
– on-line gaming systems support millions of
concurrent users, each producing multiple inputs
per second

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• Relational databases can scale and handle Big
Data but the effort is huge.

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What is NoSQL
• Non-relational next generation databases
• Different data models (Not relational)
• A collection of very different products
• Most are not using SQL for queries
• No predefined schema

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• Relational
• Divide into tables, relate into foreign keys, DB
constraints, normalized data, the Interface is SQL
• NoSQL
• Store in schemaless format, redundancy
encouraged,Interface varies and is optimized for the
implementation, no forced DB constraints.

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Document DB
MongoDB, CouchDB
Wide Column– Column Family
Cassandra, HBASE, Amazon SimpleDB
Key Value
DynamoDB, Voldemort, MemcacheDB
Graph
Neo4J, OrientDB
Many many many, many more! (http://nosql-database.org/)

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And now
let’s look at MongoDB

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• MongoDB is an open-source NoSQL-Database developed by
10gen in C++.
• Developed in 2009
• It consists of set of databases
• In which each database contains multiple collections.
• Every collection can contain different types of objects
called document
• Every document is represented as a JSON structure: a list of
key-value pairs.

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RDBMS MongoDB
Database Database
Table Collection
Row Document

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Horizontally Scalable
-Sharding
Agile
Flexible
High Performance
Application
Highly
Available
-Replica Sets
{ author: “Albin John”,
date: new Date(),
text: “MongoDB”,
tags: [“database”,
“flexible”, “JSON”]}

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• Data stored as documents (BSON)
• Schema free
• Dynamic Queries
• Capped collections
• Sharding (sometimes called partitioning) for
scalability
• Replication

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• MongoDB does not need any defined data schema.
• Every document could have different data!
name: “jeff”,
eyes: “blue”,
height: 72,
boss: “ben”}
{name: “brendan”,
aliases: [“el diablo”]}
name: “ben”,
hat: ”yes”}
{name: “matt”,
pizza: “DiGiorno”,
height: 72,
boss: 555.555.1212}
{name: “will”,
eyes: “blue”,
birthplace: “NY”,
aliases: [“bill”, “la
ciacco”],
gender: ”???”,
boss: ”ben”}

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• JSON (Java Script Object Notation)-exchange and store data
• schemaless
• Excellent performance
• MongoDB actually use BSON (Binary JSON).

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• Work with data in BSON is same as in JSON.
• It is serialized into a special binary encoded format

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• Run a query without planning for it in advance
• Like SQL queries in an RDBMS
• Wonder why listed as a feature?
• Not all NoSQL databases support dynamic queries
(CouchDB biggest “competitor”)

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• Fixed-size collections called capped collections
• Use the db.createCollection command and marked it as
capped
//limit our capped collection to 2 megabyte
db.createCollection(’logs’, {capped: true, size: 2097152})
• When it reaches 2MB limit, old documents are
automatically removed

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• Scale up, vertical scaling
Increasing server capacity (more CPU, RAM)
Managing is hard, possible down times
• Scale out, horizontal scaling
Adding servers
No single point of failure cause whole system (servers fail often, thus
replication)

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• MongoDB provides horizontal scale-out for
databases using a technique called sharding
• MongoDB distributes data across multiple physical
partitions called shards(mongod).

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Manual sharding :
application maintains connections to several completely
independent database servers
storing different data on different servers
querying against the appropriate server to get data back
Autosharding:
 which eliminates some of the administrative headaches of
manual sharding.
• It handles splitting up data and rebalancing automatically.

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• Collections  smaller chunks
• Chunks distributed across shards
• Each shard is responsible for a subset of the total data
set
• Application don’t want to know what shard has what
data
• So run a routing process called mongos in front of the
shards
• It knows where all of the data is located, so applications
can connect to it
• It connected to a normal mongod

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• Replication via replica set
• Replica sets distribute data across machines for
– redundancy
– automate failover

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• It consist of
• exactly one primary node
• one or more secondary nodes
• It primary node can accept both reads and writes
• The secondary nodes are read-only

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Replication
Read
Write
Read
Read
Driver
Primary
Priority 1
Secondary
Priority 1
Secondary
Priority 1
Secondary
Priority 0Read

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Read
Write
Read
Read
Driver
Primary
Priority 1
Secondary
Priority 1
Secondary
Priority 1
Secondary
Priority 0Read

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Read
Write
Read
Read
Driver
Primary
Priority 1
Secondary
Priority 1
Secondary
Priority 1
Secondary
Priority 0Read
I last synced
1 seconds ago
I last synced
3 seconds ago

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Write
Read
Read
Driver
Primary
Priority 1
Primary
Priority 1
Secondary
Priority 1
Secondary
Priority 0Read
Automatic
Leader Election

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Write
Read
Read
Driver
Secondary
Priority 1
Primary
Priority 1
Secondary
Priority 1
Secondary
Priority 0Read
Read

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Primary
Secondary
Secondary
Primary
Secondary
Secondary
Primary
Secondary
Secondary
Primary
Secondary
Secondary
Key Range
0..30
Key Range
31..60
Key Range
61..90
Key Range
91.. 100
MongoS MongoS MongoS Config
Config
Config
Clients

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• MongoDB is the database for today's applications:
– innovative
– fast time-to-market
– globally scalable
– inexpensive to operate

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