2. What Is SQL?
SQL is used to communicate with a database
SQL is used to access and manipulate
databases
SQL stands for Structured Query Language
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3. What Can SQL do?
SQL can execute queries against a database
SQL can retrieve data from a database
SQL can insert records in a database
SQL can update records in a database
SQL can delete records from a database
SQL can create new databases
SQL can create new tables in a database
SQL can create stored procedures in a database
SQL can create views in a database
SQL can set permissions on tables, procedures, and
views
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4. SQL Used
An RDBMS database program (i.e. MS Access, SQL
Server, MySQL)
To use a server-side scripting language, like PHP or ASP
To use SQL to get the data we want
To use HTML / CSS
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5. RDBMS
RDBMS stands for Relational Database Management
System.
RDBMS is the basis for SQL, and for all modern database
systems such as MS SQL Server, IBM DB2, Oracle, MySQL,
and Microsoft Access.
The data in RDBMS is stored in database objects called
tables.
A table is a collection of related data entries and it
consists of columns and rows.
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6. Why Is SQL Important?
It is mature and well understood
It can handle relational data models
It can handle hierarchical data models
It can handle unstructured data models
It can handle complex/nested transactions
It is an ISO / IEC standard
It can be used centralized applications (e.g. ERP)
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8. What Is NoSQL?
Originally referring to "Non SQL" or "Not Only SQL"
or "Non Relational"
NoSQL databases are sometimes referred to as
cloud databases, non-relational databases, Big
Data databases
A NoSQL database environment is, simply put, a
non-relational and largely distributed database
system that enables rapid, ad-hoc organization
and analysis of extremely high-volume, disparate
data types.
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9. Types of NoSQL Databases
Graph database
Key-Value store
Column store
Document database
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10. Why NoSQL?
The Growth of Big Data
Continuous Data Availability
Real Location Independence
Modern Transactional Capabilities
Flexible Data Models
Better Architecture
Analytics and Business Intelligence
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11. Evaluating NoSQL databases
Data model Performance Scalability Flexibility Complexity Functionality
Key-value
store
High High High None
Variable
(None)
Column
Store
High High Moderate Low Minimal
Document
Store
High
Variable
(High)
High Low
Variable
(Low)
Graph
Database
Variable Variable High High
Graph
Theory
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13. Difference between SQL and
NoSQL
SQL NoSQL
Store related data in tables Store related data in JSON-like, name-value documents
Require a schema which defines tables prior to use Can store data without specifying a schema
Encourage normalization to reduce data redundancy
Must usually be denormalized so information about an
item is contained in a single document
Support table joins to retrieve related data from
multiple tables in a single command
Should not require joins (presuming denormalized
documents are used)
Implement data integrity rules
Permit any data to be saved anywhere at any time
without verification
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14. Difference between SQL and
NoSQL
SQL NoSQL
Provide transactions to guarantee two or more
updates succeed or fail as an atomic unit
Guarantee updates to a single document — but not
multiple documents
Can be scaled (with some effort) Provide excellent performance and scalability
Use a powerful declarative language for querying Use JSON data objects for querying
Offer plenty of support, expertise and tools. It is a newer, exciting technology.
MySQL, Postgres, Microsoft SQL Server, Oracle
Database
MongoDB, Cassandra, HBase, Neo4j
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15. Difference between SQL and
NoSQL
SQL NoSQL
One type with minor variations
Many different types including key-value stores,
document databases, wide-column stores, and
graph databases
Mix of open-source (e.g., Postgres, MySQL) and
closed source (e.g., Oracle Database)
Open-source
Specific language using Select, Insert, and Update
statements, e.g. SELECT fields FROM table
WHERE etc.
Through object-oriented APIs
Can be configured for strong consistency
Depends on product.
Some provide strong consistency (e.g., MongoDB,
with tunable consistency for reads) whereas others
offer eventual consistency (e.g., Cassandra).
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16. Why Is NoSQL Important?
Large volumes of rapidly changing structured,
semi-structured, and unstructured data
Agile sprints, quick schema iteration, and
frequent code pushes
Object-oriented programming that is easy to use
and flexible
Geographically distributed scale-out architecture
instead of expensive, monolithic architecture
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17. Conclusion
All the choice provided by the rise of NoSQL
databases does not mean the demise of
RDBMS databases. We are entering an era of
polyglot persistence, a technique that uses
different data storage technologies to
handle varying data storage needs. Polyglot
persistence can apply across an enterprise or
within a single application.
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