MongoDB is a document-oriented database that stores data in JSON-like documents. It does not use a schema and allows dynamic typing. Documents can be embedded within other documents to create complex data structures. MongoDB provides high availability through replication and automatic failover. It scales easily through auto-sharding which partitions data across servers. MongoDB supports many programming languages and frameworks and can handle over a million operations per second. It is a good choice for applications that need to scale easily and work with dynamic or complex data structures.

1. An Introduction
Deepak Kumar | @_deepak0

2. An Introduction
Deepak Kumar | @_deepak0

3. MongoDB
● Document oriented
a. Objects are mapped as documents
b. Documents can be embedded
c. Dynamically typed
● No Schema
● High availability
a. Replication through sharding.
b. Automatic failover
● Easy scaling
a. Auto shrading ( auto partitioning data across servers)
● Speed

4. Programming Language Support
Supported by all the popular programming
languages (C++, Java, Python, Ruby, Go, Haskel
etc...) and web frameworks ( Rails, Django etc).

5. Interesting Fact
There are MongoDB systems that exceed one
million operations per second.

6. MongoDB document model
Key Key Value
Field
Document
Collection
Database

7. Data Types Supported
● String
● Number
● Boolean
● Date
● Null
● Array
● Object ID
● Binary data
● Regular Expression

8. Why should we use Mongodb
● Easy to scale
● Coding velocity (agility)
● No impedance mismatch
● Allows dynamic schema ( No Schema, agility)
● Easier to store and manipulate polymorphic data
● Variety of Indexing
● A MapReduce tool.

9. Impedance Mismatch
In object relational mapping an object in
programming language is mapped to a record in
database. So if the data is simple and database
support it then there is no mismatch.
But if the data is polymorphic and have unsupported
types then the mapping will be difficult which
causes a impedance mismatch.
In mongodb data is of JSON format so it can map
well to the object.

10. Where should we avoid MongoDB
● Problems with SQL support.
● Systems with heavy emphasis on complex
transactions such as banking.
● Data Warehousing whose underlying database
are schema based.

11. Indexing
● Indexing can be done on a field
● Indexing can be done on an embedded object.
● Sparse indexing - Indexing based existence of
field.
● TTL index
● Geospatial Index ( Location based access)
● Geohaystack index (Bucket based small regions)

12. MongoDB/ Components
● Mongod => Database Process
● Mongoes => Shrading Controller
● Mongo => Database Shell ( javascript shell)

13. MongoDB/Utilities
● mongodump => Dump tool for backup and
snapshot
● mongorestore => Restore a dump
● mongoexport => Export a single collection to
JSON or CSV
● mongoimport => Import from JSON or CSV
● mongofiles => Utility for putting and getting
files from MongoDB GridFS
● mongostat => Performance statistics tool

14. Single Server Configuration
● Install mongodb
● create a database directory
eg: mkdir -p /data/db
● create a configuration file (optional)
eg: /etc/mongodb.conf
● start the mongodb server
sudo mongod -f /etc/mongodb.conf OR use init
script.
● connect to the database using javascript console
mongo
You will get connected to test database.

15. MongoDB Multiserver Configuration

16. Third party Software Used With
MogoDB
Boost => Portable open source C++ libraries.
V8 => Javascript runtime.
PCRE => Perl compatible regular expression.
MD5 => Message Digest Algorithm
Snappy => fast compression and decompression tool

17. Edda - Admin Tool
● Edda provides a graphical visualization of
mongodb servers .
● Edda provides an easy way to check the status in
multiserver configuration.

18. Companies Using MongoDB
● Foursquare
● MTV networks
● Disney
● Customlnk
● Sourceforge
● Wowmakers
● and many others ....

19. Thanks

20. Questions ?