HRDC_SEMINAR_Database management systems Today

Database Management Today: New
strategies and Technologies

Dr. S.L.JAYALAKSHMI
Assistant Professor Senior Grade-1
School of Computer Science and Engineering (SCOPE)
VIT University, Chennai Campus

1 18-06-2022

Outline

 Database Management Systems (DBMS)
 Databases that bridge SQL and NoSQL
 Databases on the Cloud
 AI in Database Management System
 Augmented Database Management
 Graph Database
 Big Data
 An Increased focus on Security
 Current landscape for database management systems
 Case study

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Database Management Systems (DBMS)

 Data 18-06-2022
 Database
 Mini-world
 Database management System (DBMS)

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Basic Definitions

 Data

Known facts that can be recorded and have an implicit
meaning.

Image Source: https://dev.to/salonix__/dbms-database-management-system-4mnf 18-06-2022

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Basic Definitions

 Database

• A database is a collection of related data
which represents some aspect of the real
world.

Image Source: https://images.app.goo.gl/SC9RsQtbHKLXfgPy5

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Basic Definitions

Image Source: https://images.app.goo.gl/bb5B1huyJH82G1Rk9  Mini-World

6 Some part of the real world about which data is
stored in a database. For example, student grades and
transcripts at a university.

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Basic Definitions

 Database Management System

A software package/ system to facilitate the creation and maintenance of a
computerized database.

Image Source: https://images.app.goo.gl/NTjboXo3m5Urojj76 18-06-2022

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Basics

 More specifically, a DBMS is a general purpose software system facilitating
each of the following (with respect to a database):
 Definition: specifying data types (and other constraints to which the
data must conform) and data organization
 Construction: the process of storing the data on some medium (e.g.,
magnetic disk) that is controlled by the DBMS
 Manipulation: querying, updating, report generation
 Sharing: allowing multiple users and programs to access the database
"simultaneously"
 System protection: preventing database from becoming corrupted
when hardware or software failures occur
 Security protection: preventing unauthorized or malicious access to
database

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Example of a Database

 Mini-world for the example:

 Part of a UNIVERSITY
environment.

 Some mini-world entities:

 STUDENTs
 COURSEs
 SECTIONs (of COURSEs)
 (academic) DEPARTMENTs
 INSTRUCTORs

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Example of a Database

 Some mini-world relationships:

 SECTIONs are of specific COURSEs
 STUDENTs take SECTIONs
 COURSEs have prerequisite COURSEs
 INSTRUCTORs teach SECTIONs
 COURSEs are offered by DEPARTMENTs
 STUDENTs major in DEPARTMENTs

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Example of a Database

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Image Source: Ramez Elmasri and Shamkant B. Navathe

Example of a Database

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Image Source: Ramez Elmasri and Shamkant B. Navathe

Characteristics of
Database Approach

 Self-describing nature of a database system:
 A DBMS catalog stores the description of a particular
database (e.g. data structures, types, and constraints)
 The description is called meta-data (Data
Dictionary).
 This allows the DBMS software to work with different
database applications.

Iinmteagr1veieS3wousrce: https://www.quora.com/How-should-I-write-my-self-description-in-SSB-

Characteristics of Database
Approach

 Insulation between programs and data:

 Called program-data independence.
 Allows changing data structures and storage

organization without having to change the DBMS
access programs.

Imag1e S4ource: https://www.indiamart.com/proddetail/insulation-tape-19584466491.html

Characteristics of Database Approach

 Data Abstraction:
 A data model is used to hide storage details and present the users with a
conceptual view of the database.
 Programs refer to the data model constructs rather than data storage details.

Imag1e5Source: https://www.hitechnectar.com/blogs/data-abstraction-level/

Characteristics of Database Approach

 Support of multiple views of the data:

 Each user may see a different view of the database,
which describes only the data of interest to that user.

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Characteristics of Database Approach

 Sharing of data and multi-user transaction
processing:

 Allowing a set of concurrent users to retrieve from and to
update the database.

 Concurrency control within the DBMS guarantees that each
transaction is correctly executed or aborted

 Recovery subsystem ensures each completed transaction has its
effect permanently recorded in the database

 OLTP (Online Transaction Processing) is a major part of database
applications.This allows hundreds of concurrent transactions to
execute per second.

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Popular DBMS Software 18-06-2022

 MySQL
 Microsoft Access
 Oracle
 PostgreSQL
 dBASE
 FoxPro
 SQLite
 IBM DB2
 LibreOffice Base
 MariaDB
 Microsoft SQL Server etc.

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Applications of DBMS

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Types of DBMS

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Structured Query Language (SQL)

 SQL stands for Structured
Query Language.

 Initially it was called as
SEQUEL (Structured Query
English Language)

 The ANSI standard language
for the definition and
manipulation of relational
database.

 Includes data definition
language (DDL), statements
that specify and modify
database schemas.

 Includes a data
manipulation language
(DML), statements that
manipulate database
content.

21 https://images.app.goo.gl/EcKgscYnG1bAKqjD7 18-06-2022

Data Definition (Pillar of database architecture)

 Metadata describes data about data.
 Metadata clearly explains the low level structure

of data.
 Metadata highly dominates while the creation of

database.

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DDL, DQL, DML & DCL

 Data Definition Language
 Data Query Language
 Data Manipulation Language
 Data Control Language

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DDL, DQL, DML & DCL

SQL Commands

DDL DQL DML DCL

CREATE SELECT INSERT GRANT
ALTER UPDATE REVOKE
DROP DELETE
TCL: RENAME
Commit; TRUNCATE
Rollback;

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DDL, DQL, DML & DCL

 DDL Syntax :

*desc table_name; CREATE CREATE TABLE table_name (
column1 datatype,
ALTER column2 datatype,
DROP column3 datatype,
.... );

ALTER TABLE table_name
ADD column_name datatype;

DROPTABLE table_name;

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DDL, DQL, DML & DCL

 DDL Syntax :

RENAME ALTER TABLE table_name
RENAME TO new_table_name;

TRUNCATE TABLE table_name;

TRUNCATE

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DDL, DQL, DML & DCL

 DQL Syntax :

SELECT SELECT column1, column2, ...
FROM table_name;

DML Syntax :

INSERT INSERT INTO TABLE_NAME (column1,
column2, column3,...columnN)]

VALUES (value1, value2,
value3,...valueN);

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DDL, DQL, DML & DCL

 DML Syntax (Cont.) :

UPDATE UPDATE table_name
SET column1 = value1,
column2 = value2, ...
WHERE condition;

DELETE DELETE FROM table_name
WHERE condition;

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DDL, DQL, DML & DCL

 DCL Syntax :

GRANT GRANT privilege_name
ON object_name
TO {user_name |PUBLIC |role_name}
[WITH GRANT OPTION];

REVOKE REVOKE privilege_name
ON object_name
FROM {user_name |PUBLIC |role_name}

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NoSQL (Not Only SQL)

 NoSQL Database is a non-relational Data Management
System, that does not require a fixed schema. It avoids joins,
and is easy to scale.

 NoSQL is used for Big data and real-time web apps.
 For example, companies like Twitter, Facebook and Google

collect terabytes of user data every single day.
 Traditional RDBMS uses SQL syntax to store and retrieve

data for further insights.
 Instead, a NoSQL database system encompasses a wide range

of database technologies that can store structured, semi-
structured, unstructured and polymorphic data.

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NoSQL (Not Only SQL) 18-06-2022

 It falls under four main categories

1. Key-value
2. Document
3. Column oriented
4. Graph

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Key Value Pair Based

 Data is stored in key/value pairs. It KEY VALUE
is designed in such a way to handle Name xyz
lots of data and heavy load. Age 42
occupation Manager
 Key-value pair databases store data
as a hash table where each key is 18-06-2022
unique, and the value can be a
JSON, BLOB(Binary Large
Objects), string, etc.

 For example, a key-value pair may
contain a key like "Website"
associated with a value like
“Google.com".

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Document based

 Document-Oriented NoSQL DB stores and retrieves data as
a key value pair but the value part is stored as a document.

 The document is stored in JSON or XML formats.The value
is understood by the DB and can be queried.

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Document based

 The document type is mostly used for Content Management
systems(CMS), blogging platforms, real-time analytics & e-
commerce applications. It should not use for complex
transactions which require multiple operations or queries
against varying aggregate structures.

 Amazon SimpleDB, CouchDB, MongoDB, Riak, Lotus
Notes, are popular Document oriented DBMS systems.

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Column-based

 Column-oriented databases work on columns
 Every column is treated separately.Values of single column

databases are stored contiguously.

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Column-based

 They deliver high performance on aggregation queries like
SUM, COUNT, AVG, MIN etc. as the data is readily available
in a column.

 Column-based NoSQL databases are widely used to manage
data warehouses, business intelligence, CRM(Customer
Relationship Management), and Library card catalogs,

 HBase, Cassandra, Hypertable are NoSQL query examples of
column based database.

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Graph-based

 A graph type database stores entities as well the relations
amongst those entities.The entity is stored as a node with the
relationship as edges.

 An edge gives a relationship between nodes. Every node and
edge has a unique identifier.

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Graph-based

 Graph base database mostly used for social networks,
logistics, spatial data.

 Neo4J, Infinite Graph, OrientDB, FlockDB are some popular
graph-based databases.

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CAP THEOREM

 What is the CAP Theorem?

 CAP theorem is also called brewer's theorem. It states that is
impossible for a distributed data store to offer more than two
out of three guarantees

 Consistency
 Availability
 PartitionTolerance

 Eventual Consistency

 To have copies of data on multiple machines to get high
availability and scalability.

 changes made to any data item on one machine has to be
propagated to other replicas.

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SQL Vs NoSQL

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SQL Vs NoSQL

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SQL Vs NoSQL

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SQL vs NoSQL

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Comparison of No SQL databases

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Databases that bridge between SQL
and NoSQL

 NewSQL databases

 attempt to provide enterprises with the top benefits of
both relational and NoSQL databases on one platform.

 NewSQL databases attempt to combine the data consistency
benefits of traditional relational databases with the scalability of
NoSQL platforms.

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Example: NewSQL

 Google Cloud Spanner. Google describes Cloud
Spanner as "the only enterprise-grade, globally
distributed and strongly consistent database service
built for the cloud specifically to combine the benefits
of relational database structure with non-relational
horizontal scale.

 CockroachDB. Although it may not be the most
endearing product name, many industry experts
include CockroachDB in their lists of leading NewSQL
products. CockroachDB provides ACID-compliant
transactions, automatic sharding and a globally scalable
architecture.

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Example: NewSQL

 NuoDB. NuoDB is a popular NewSQL product that offers
a distributed database architecture based on its own, SQL-
based ACID-compliant DBMS engine. NuoDB's website
includes a page that provides a well-thought-out decision
tree that will help you choose a DB product based on
application needs.

 VoltDB. It is an ACID-compliant, shared-nothing, in-
memory database cluster. It's shared-nothing architecture
means it runs in memory across clusters to enable large
scalability levels.VoltDB is known for its speedy throughput
and was designed to avoid most of the operations that can
drive processing overhead in most relational databases.

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Databases on the Cloud

 Cloud computing is the delivery of on demand computer
system resources, requiring no active management and
usually includes applications such as storage and processing
power.

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Database as a Service (DBaaS)

 A DBaaS is a database cloud service that takes over the
management of the underlying infrastructure and resources cloud
databases require.

 As the cloud market leaders, AWS, Azure and Google Cloud all
offer DBaaS services in a variety of flavors.

 The database as a service AWS offerings include Amazon Relational
Database Service (RDS) and Amazon Aurora.

 NoSQL databases such as Hadoop or MongoDB, etc.
 Azure database as a services include Azure Database for

MySQL, Azure Database for PostgreSQL, and Azure SQL Database.
 Google Cloud offers Cloud SQL and Cloud Spanner for relational

databases and Cloud Bigtable, Cloud Firestore, and more for NoSQL.

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