MongoDB is a document database. It stores data in a type of JSON format called BSON.

What is MongoDB?
 Developed by 10gen
 Founded in 2007
 A document-oriented, NoSQL database
 Hash-based, schema-less database • No Data Definition Language
 In practice, this means you can store hashes with any keys and values that
you choose • Keys are a basic data type but in reality stored as strings
 Document Identifiers (_id) will be created for each document, field name
reserved by system

Cont..
 Application tracks the schema and mapping • Uses BSON format
 Based on JSON
 Written in C++
 Supports APIs (drivers) in many computer languages
 JavaScript, Python, Ruby, Perl, Java, Java Scala, C#, C++, Haskell, Erlang

Functionality of MongoDB
 Dynamic schema
 No DDL
 Document-based database
 Secondary indexes
 Query language via an API
 Atomic writes and fully-consistent reads
 If system configured that way
 Master-slave replication with automated failover (replica sets)
 Built-in horizontal scaling via automated range-based partitioning of data
(sharding)
 No joins nor transactions

Why use MongoDB?
 Simple queries
 Functionality provided applicable to most web applications
 Easy and fast integration of data
 No ERD diagram
 Not well suited for heavy and complex transactions systems

MongoDB: CAP approach
 Focus on Consistency and Partition tolerance
 Consistency
 all replicas contain the same version of the data
 Availability
 system remains operational on failing nodes • Partition tolarence
 multiple entry points
 system remains operational on system split

MongoDB: Hierarchical Objects
• A MongoDB instance may have zero or more ‘databases’
• A database may have zero or more ‘collections’.
• A collection may have zero or more ‘documents’.
• A document may have one or more ‘fields’.
• MongoDB ‘Indexes’ function much like their RDBMS counterparts.

MongoDB Processes and configuration
 Mongod – Database instance
 Mongos - Sharding processes
 Analogous to a database router.
 Processes all requests
 Decides how many and which mongodsshould receive the query
 Mongos collates the results, and sends it back to the client.
 Mongo – an interactive shell ( a client)
 Fully functional JavaScript environment for use with a MongoDB
 You can have one mongos for the whole system no matter how many
mongods you have

Choices made for Design of MongoDB
 Scale horizontally over commodity hardware
 Lots of relatively inexpensive servers
 Keep the functionality that works well in RDBMSs – Ad hoc queries –
Fully featured indexes – Secondary indexes
 What doesn’t distribute well in RDB?
– Long running multi-row transactions
– Joins
– Both artifacts of the relational data model (row x column)

BSON format
 Binary-encoded serialization of JSON-like documents
 Zero or more key/value pairs are stored as a single entity
 Each entry consists of a field name, a data type, and a value
 Large elements in a BSON document are prefixed with a length field to
facilitate scanning

JSON format
 Data is in name / value pairs
 A name/value pair consists of a field name followed by a colon, followed
by a value: • Example: “name”: “R2-D2”
 Data is separated by commas
Example: “name”: “R2-D2”, race : “Droid” • Curly braces hold
objects
Example: {“name”: “R2-D2”, race : “Droid”, affiliation: “rebels”}
 An array is stored in brackets []
Example [ {“name”: “R2-D2”, race : “Droid”, affiliation: “rebels”},
 {“name”: “Yoda”, affiliation: “rebels”} ]

MongoDB Features
• Document-Oriented storage
• Full Index Support
• Replication & High Availability
• Auto-Sharding
• Querying
• Fast In-Place Updates
• Map/Reduce functionality

Index Functionality
 B+ tree indexes
 An index is automatically created on the _id field (the
primary key)
 Users can create other indexes to improve query performance
or to enforce Unique values for a particular field
 Supports single field index as well as Compound index
 Like SQL order of the fields in a compound index matters
 If you index a field that holds an array value, MongoDB
creates separate index entries for every element of the array.

Cont..
• Sparse property of an index ensures that the index only contain entries for
documents that have the indexed field. (so ignore records that do not have
the field defined)
• If an index is both unique and sparse – then the system will reject records
that have a duplicate key value but allow records that do not have the
indexed field defined

CRUD operations
• Create
db.collection.insert( )
db.collection.save( )
db.collection.update( , , { upsert: true } )
• Read
db.collection.find( , )
db.collection.findOne( , )
• Update
db.collection.update( , , )
• Delete
db.collection.remove( , )

Aggregated functionality
 Aggregation framework provides SQL-like aggregation functionality
 Pipeline documents from a collection pass through an aggregation
pipeline, which transforms these objects as they pass through
 Expressions produce output documents based on calculations performed on
input documents
 Example db.parts.aggregate ( {$group : {_id: type, totalquantity : { $sum:
quanity} } } )

Map reduce functionality
 Performs complex aggregator functions given a collection of keys, value
pairs
 Must provide at least a map function, reduction function and a name of the
result set
 db.collection.mapReduce( , , { out: , query: , sort: , limit: , finalize: , scope:
, jsMode: , verbose: } )

Indexes: High performance read
 Typically used for frequently used queries
 Necessary when the total size of the documents exceeds the amount of
available RAM.
 Defined on the collection level
 Can be defined on 1 or more fields
 Composite index (SQL) Compound index (MongoDB)

 B-tree index
 Only 1 index can be used by the query optimizer when retrieving data

Replication of data
 Ensures redundancy, backup, and automatic failover
 Recovery manager in the RDMS
 Replication occurs through groups of servers known as replica sets
 Primary set – set of servers that client tasks direct updates to
 Secondary set – set of servers used for duplication of data

Consistency of data
 All read operations issued to the primary of a replica set are consistent
with the last write operation
 Reads to a primary have strict consistency
 Reads reflect the latest changes to the data Reads to a secondary have
eventual consistency
 Updates propagate gradually

MongoDB is a document database. It stores data in a type of JSON format called BSON.

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