nosql [Autosaved].pptx

NoSQL
 Semi-structured data is also an important element of many NoSQL
 (“not only SQL”) databases.
 NoSQL databases differ from relational databases because they do not separate
the organization (schema) from the data.
 This makes NoSQL a better choice to store information that does not easily fit into
the record and table format, such as text with varying lengths.
 It also allows for easier data exchange between databases.
 Some newer NoSQL databases like MongoDB and Couchbase also incorporate
semi-structured documents by natively storing them in the JSON format.
Prof.Indrani Sen MCA,MPhil Computer Science

What is NoSQL Database?
 NoSQL databases basically called as Not Only SQL database.
 These databases are non-relational database systems used for storing and
retrieving data.
 Nowadays NoSQL Databases are predominantly utilized as real-time based web
applications.
 NoSQL databases can therefore be called as Big Data databases or Cloud
databases.
 NoSQL Databases are faster in compared to SQL Databases and thus it makes
major part of Data applications.

 Database design in relational models uses primary and foreign keys and follows
strict constraints when the tables are created.
 The main motto of NoSQL is that the relational databases are good for smaller
data storage requirements,
 but “big data” are mostly used to manage large queries.
 To properly manage big data queries NoSQL databases are appropriate which
work differently than the relational databases.

NoSQL features Result
Big Data types Structured,
unstructured and
semi-structured
Scalability Excellent
Biggest NoSQL
advantages
Large volumes of data,
dynamic schemas,
replication, auto-
sharding

Why are NoSQL Databases so popular?
 Elastic scalability – These databases are highly scalable and allow adding more hardware.
 These are implemented to increase customers and provide service as per there requirement.
 Architecture based – Lesser failures or system downtimes as these are continuously available for business-
critical applications.
 Linear-scale performance – These are linearly scalable which increase the throughput of system which is
directly proportional to the number of nodes in the cluster. Therefore it helps to maintain a quick
response time.
 Flexibility in data maintenance – The data storage includes: structured, semi-structured, and unstructured.
 The changes are done as per our requirements.
 Easy data distribution – Distribution of data can be replicated across multiple data centers.
 Fast writes – These databases are designed to run on cheap commodity hardware. They perform write
operations in blazingly fast speed and store hundreds of terabytes of data, without affecting the read
efficiency.

CouchDB
 CouchDB is an Open Source NoSQL Database based on JSON to stores data and
JavaScript in the form of query language.
 CouchDB is a multi-version controlling system for avoiding the blockage of the DB
file scripting.
 It has been ranked as the best database in the year 2016 on the basis of its highest
popularity among all the NoSQL Databases.

MongoDB
 MongoDB is the most popular among NoSQL Databases which is a free and open-
source document-oriented database program.
 It is a scalable and accessible database.
 It is prescribed in C++ but uses JSON-like documents with schemas as JavaScript
can be utilized as the query language.
 MongoDB scales horizontally which is preferable in JavaScript frameworks.

Cassandra
 Cassandra is a distributed data storage system from Apache for handling very large amounts of
structured data and highly scalable.
 Essentially, these data are widely used across many commodity servers, providing high availability
with no failure till now.
 It gives you the maximal flexibility for distribution of data.
 It allows adding data storage to your service online and makes your task much easier.
 There is no scope for complex configuration as all the nodes in a cluster are same.
 Cassandra is java based programming language which supports MapReduce on Apache Hadoop.
 Cassandra Query Language (CQL) is an SQL-like language for querying Cassandra Database.

Properties
 One such approach is the property graph model, where data is organized as
nodes, relationships, and properties
 (data stored on the nodes or relationships).
 Nodes are the entities in the graph.
 They can hold any number of attributes (key-value pairs) called properties.
 Nodes can be tagged with labels, representing their different roles in your
domain.
 Relationships provide directed, named, semantically-relevant connections between
two node entities (e.g. Member ISSUE_RETURN Book).

MongoDB
MONGODB IS A CROSS-PLATFORM, DOCUMENT ORIENTED DATABASE THAT
PROVIDES, HIGH PERFORMANCE, HIGH AVAILABILITY, AND EASY
SCALABILITY. MONGODB WORKS ON CONCEPT OF COLLECTION AND
DOCUMENT.

Mongodb installation
MongoDB Community Download | MongoDB

Use your windows UserId and password( if password
is not there you have to create)

If you are installing as a network service uncheck this in
windows 10

Install the interface
Download Studio 3T for MongoDB | Windows,
macOS & Linux

Creating database
 The use Command
 MongoDB
 use DATABASE_NAME is used to create database. The command will create a new
database if it doesn't exist, otherwise it will return the existing database.

 >use mydb
switched to db mydb

To list databases
 >show dbs
 local 0.78125GB
 mydb 0.23012GB
 test 0.23012GB

Deleting database
 The dropDatabase() Method
 db.dropDatabase() command is used to drop a existing database.
 Syntax
 db.dropDatabase()
 This will delete the selected database.
 If you have not selected any database, then it will delete default 'test' database.

Collections
 MongoDB stores documents in collections.
 Collections are analogous to tables in relational databases.
 Create a Collection
 If a collection does not exist, MongoDB creates the collection when you first store
data for that collection

Creating collection
 The createCollection() Method
 MongoDB db.createCollection(name, options) is used to create collection.
 Syntax
 db.createCollection(name, options) In the command, name is name of collection
to be created. Options is a document and is used to specify configuration of
collection likememory size etc.

List collections
 >db.createCollection("mycollection")
 using the command show collections.
 >show collections
 In MongoDB, you don't need to create collection. MongoDB creates collection
automatically, when you insert some document.

Documents
 A record in MongoDB is a document, which is a data structure composed of field and value pairs.
 MongoDB documents are similar to JavaScript Object Notation objects but use a variant called Binary
JSON (BSON) that accommodates more data types.
 The fields in documents are akin to the columns in a relational database, and the values they contain can
be a variety of data types,
 including other documents, arrays and arrays of documents
 Documents, which also must incorporate a primary key as a unique identifier, are the basic unit of data in
MongoDB.
 Collections contain sets of documents and function as the equivalent of relational database tables.
 Collections can contain any type of data, but the restriction is the data in a collection cannot be spread
across different databases.

Advantages of mongodb
 Flexible schema
 No need of joins
 Faster queries
 Document based model
 Efficient for Haddoop implementation

Database
 Database is a physical container for
collections. Each database gets its own set of
files on the file system.
 A single MongoDB server typically has
multiple databases.

Collection
 Collection is a group of MongoDB documents.
 It is the equivalent of an RDBMS table.
 A collection exists within a single database.
 Collections do not enforce a schema.
 Documents within a collection can have different fields.
 Typically, all documents in a collection are of similar or related purpose.

 [Recipe_details
 {recipe_id ,
 Name:Lucknowi Mutton Biryani,
 summary:Lucknowi Mutton Biryani is a very popular North Indian recipe. It is different
from the basic biryanis as it come straight from the Nawabs and is the soul of every
party. It is made from cashewnut paste, saffron, curd, star anise and mace powder that
give it an amazing flavour. In this delightful recipe, the process of marination is very
important. The longer you marinate the meat, the better is the taste of the biryani. It is
also important to soak the rice in water for sometime,
 date_publish: 2017-05-15T15:45:37+05:30
 category:Main
 Cuisine:Awadhi
 preptime:PT15M
 Tottime:PT40M
 Yield:4 Servings

MongoDB
 [Recipe_details {recipe_id , title,summary,author,
date_publish,category,cuisine,preptime,cooktime,
yield,ingredient_list,instruction_list,
 [recipe_qty{ qty,unit,Ingredient_name, ref_id_list{ingredient_name ,
feature_list,category} ]
 Instruction[ {method_name, time, tool, [Ingredient{ingredient_name ,
feature_list ,category} ]
 }]

Library database

Transactions
 Transactions in a database environment have two main purposes:-
 Reliability of data: In case of unpredictable circumstances such as power failures or
system failures while a database is getting updated or being read,
 the transactions should ensure to give us consistent and accurate data.
 Concurrent Access of data:When more than one user or application programs are
trying to access the same data,
 the transactions should provide isolation between the programs accessing a database
concurrently.
 Otherwise concurrent read or write operations to a database may lead to inconsistent
or erronaeous data.

Phases of transaction
 Begin the transaction.
 Execute a set of data manipulations and/or queries.
 If no errors occur then commit the transaction and end it.
 If errors occur then rollback the transaction and end it.

Atomicity
 A transaction is an atomic unit of processing;
 it is either performed in its entirety or not performed at all.
 The atomicity property requires that we execute a transaction to completion.
 It is the responsibility of the recovery subsystem of a DBMS to ensure atomicity.
 If a transaction fails to complete for some reason, such as a system crash in the
midst of transaction execution,
 the recovery technique must undo any effects of the transaction on the database.

ATM(withdrawal) Database Recovery Manager
Account_Balance =
Account_Balance -
Withdraw _amt
Account
debited
Crash/Transaction
Error
Transaction
rollback
Account_Balance=
Account_Balance +
Withdraw _amt
Account
credited/
reversed

Consistency preservation:
 The DBMS has to ensure that the transaction preserves data consistency in a
database and does not violate any integrity constraints .
 A database program should be written in a way that guarantees that, if the
database is in a consistent state before executing the transaction,
 it will be in a consistent state after the complete execution of the transaction,
 assuming that no interference with other transactions occurs

 Consider an account hoder tries to withdraw an amount from his Account where
withdraw_amt is greater than the balance,
 then the transaction should not cause a change in the database as the action will
violate a constraint in the database .
 So the DBMS programmers must ensure that such a constraint should exist which
will not allow the database to go in an inconsistent state.
 A Bank employee tries to open an Account with the same Account_no which
already has been assigned to another Account holder,
 in this case the transaction should ensure that the Account_no should not be
duplicated and hence maintain database integrity.

Isolation:
 A transaction should appear as though it is being executed in isolation from other
transactions.
 That is, the execution of a transaction should not be interfered with by any other
transactions executing concurrently.

Durability or permanency
 The changes applied to the database by a committed transaction must be
permanent in the database.
 These changes must not be lost because of any failure.
 For example ,Consider the Account_holder is transferring funds from Account A to
Account B then under the following conditions,
 the changes should be permanent and cannot be reversed
 even if the application crashes
 or an error occurs
 or the user decides to cancel the transaction after the transaction is over

Some Transaction Primitives
Examples of primitives for transactions.
Primitive Description
BEGIN_TRANSACTION Make the start of a transaction
END_TRANSACTION Terminate the transaction and try to commit
ABORT_TRANSACTION Kill the transaction and restore the old values
READ Read data from a file, a table, etc.
WRITE Write data to a file, a table, etc.

Base Model:
 The rise in popularity of NoSQL databases provided a flexible and fluidity with
ease to manipulate data and as a result,
 a new database model was designed, reflecting these properties.
 The acronym BASE is slightly more confusing than ACID but however, the words
behind it suggest ways in which the BASE model is different

BASE
1. Basically Available:
2. Instead of making it compulsory for immediate consistency,
3. BASE-modelled NoSQL databases will ensure the availability of data by spreading
and replicating it across the nodes of the database cluster.
4. Soft State:
5. Due to the lack of immediate consistency, the data values may change over time.
6. Eventually Consistent:
7. The fact that BASE does not obligates immediate consistency but it does not
mean that it never achieves it.
8. However, until it does, the data reads are still possible (even though they might
not reflect reality).

S. No Criteria ACID BASE
1. Simplicity Simple Complex
2. Focus Commits Best attempt
3. Maintenance High Low
4. Consistency Of Data Strong Weak/Loose
5. Concurrency scheme Nested Transactions Close to answer
6. Scaling Vertical Horizontal
7. Implementation Easy to implement Difficult to implement
8. Upgrade Harder to upgrade Easy to upgrade
9. Type of database Robust Simple
10. Type of code Simple Harder
11. Time required for completion Less time More time.
12. Examples Oracle, MySQL, SQL Server, etc.
DynamoDB, Cassandra, CouchDB,
SimpleDB etc.
ACID vs BASE

CAP Theorem
What is the CAP theorem?
• The CAP Theorem is comprised of three components
(hence its name) as they relate to distributed data stores:
• Consistency. All reads receive the most recent write or an
error.
• Availability. All reads contain data, but it might not be the
most recent.
• Partition Tolerance. The system continues to operate
despite network failures (i.e.; dropped partitions, slow
network connections, or unavailable network connections
between nodes.)

NoSQL Database
• NoSQL databases do not require a schema, and don’t enforce relations between tables.
• All its documents are JSON documents, which are complete entities one can readily read and understand.
• They are widely recognized for:
• Ease-of-use
• Scalable performance
• Strong resilience
• Wide availability
Examples of NoSQL databases include:
• Cloud Firestore
• Firebase Real-time DB
• MongoDB
• MarkLogic
• Couchbase
• CloudDB
• Amazon DynamoDB

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