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COMPILATION of all ENTRIES of any particular TYPE of entry in the database is CALLED ENTITY Set.

Compilation of all entries of any particular type of entry in the database is called Entity Set.

It can be DEFINED as being a ‘THING’ with an INDEPENDENT existence in the REAL world.

It can be defined as being a ‘thing’ with an independent existence in the real world.

Compilations of objects make up this model in which values are stored within INSTANCE variables which is inside the object. The object itself comprises BODIES of object for its OPERATION which are CALLED methods. Objects containing same KIND of variables and methods are called classes.

Compilations of objects make up this model in which values are stored within instance variables which is inside the object. The object itself comprises bodies of object for its operation which are called methods. Objects containing same kind of variables and methods are called classes.

The various transaction PHASES are:

• ANALYSIS PHASE.
• Redo Phase.
• Undo Phase.

The various transaction phases are:

Atomicity: It’s an all or none CONCEPT which enables the USER to be assured of incomplete transactions to be TAKEN care of. The actions involving incomplete transactions are LEFT undone in DBMS.

Aggregation: The collected entities and their relationship are aggregated in this model. It is mainly used in EXPRESSING relationships within relationships.

Atomicity: It’s an all or none concept which enables the user to be assured of incomplete transactions to be taken care of. The actions involving incomplete transactions are left undone in DBMS.

Aggregation: The collected entities and their relationship are aggregated in this model. It is mainly used in expressing relationships within relationships.

Division of LOGICAL DATABASE into independent complete units for improving its management, AVAILABILITY and PERFORMANCE is called Database PARTITIONING.

Division of logical database into independent complete units for improving its management, availability and performance is called Database partitioning.

Splitting of one table which is large into smaller database entities LOGICALLY is called database PARTITIONING. Its benefits are:

• To improve query performance in situations dramatically when mostly rows which are heavily accessed are in one PARTITION.
• ACCESSING large PARTS of a single partition.
• Slower and cheaper storage media can be used for data which is seldom used.

Splitting of one table which is large into smaller database entities logically is called database partitioning. Its benefits are:

DBMS ALONG with DATABASE is CALLED Database SYSTEM.

DBMS along with database is called Database system.

DDL STATEMENTS are interpreted and RECORDED in tables CALLED METADATA.

DDL statements are interpreted and recorded in tables called metadata.

QUERY Evaluation Engine EXECUTES the low-level INSTRUCTIONS that are generated by the COMPILER.

Query Evaluation Engine executes the low-level instructions that are generated by the compiler.

Fragmentation can be DEFINED as a database FEATURE of server that promotes control on DATA which is STORED at table level by the user.

Fragmentation can be defined as a database feature of server that promotes control on data which is stored at table level by the user.

Fill Factor can be DEFINED as being that value which defines the percentage of LEFT SPACE on every leaf-level PAGE that is to be packed with data. 100 is the DEFAULT value of Fill Factor.

Fill Factor can be defined as being that value which defines the percentage of left space on every leaf-level page that is to be packed with data. 100 is the default value of Fill Factor.

ITERATING over all the table ROWS is called Table Scan while iterating over all the index ITEMS is DEFINED as Index Scan.

Iterating over all the table rows is called Table Scan while iterating over all the index items is defined as Index Scan.

A data structure in the form of tree which stores sorted data and searches, insertions, SEQUENTIAL ACCESS and deletions are allowed in LOGARITHMIC time.

A data structure in the form of tree which stores sorted data and searches, insertions, sequential access and deletions are allowed in logarithmic time.

Executive PLAN can be DEFINED as:

• SQL Server caches collected procedure or the plan of query execution and used THEREAFTER by subsequent CALLS.
• An important feature in RELATION to performance enhancement.
• Data execution plan can be viewed textually or graphically.

Executive plan can be defined as:

Ways to efficiently code TRANSACTIONS:

• User input should not be allowed while transactions.
• While browsing, transactions must not be opened of data.
• Transactions must be kept as small as possible.
• LOWER transaction SEGREGATION levels.
• LEAST INFORMATION of data must be accessed while transacting.

Ways to efficiently code transactions:

The disadvantages of QUERY are:

• No indexes
• Stored procedures are excessively compiled.
• Triggers and procedures are WITHOUT SET NOCOUNT ON.
• COMPLICATED joins making up inadequately written query.
• Cursors and temporary TABLES showcase a bad presentation.

The disadvantages of query are:

Index hunting helps in improving the speed as WELL as the QUERY performance of database. The followed measures are achieved to do that:

• The query optimizer is used to coordinate the study of queries with the workload and the best USE of queries suggested based on this.
• Index, query distribution along with their performance is observed to check the effect.
• Tuning databases to a small collection of problem queries is also RECOMMENDED.

Index hunting helps in improving the speed as well as the query performance of database. The followed measures are achieved to do that:

INDEXES help in IMPROVING the speed as well as the QUERY performance of database. The procedure of boosting the collection of indexes is named as Index HUNTING.

Indexes help in improving the speed as well as the query performance of database. The procedure of boosting the collection of indexes is named as Index hunting.

Joins help in explaining the relation between different TABLES. They also enable you to select data with relation to data in another table.

The various types are:

INNER JOINs: Blank rows are LEFT in the middle while more than equal to two tables are joined.

OUTER JOINs: Divided into Left Outer Join and RIGHT Outer Join. Blank rows are left at the SPECIFIED side by joining tables in other side.
Other joins are CROSS JOINs, NATURAL JOINs, EQUI JOIN and NON-EQUI JOIN.

Joins help in explaining the relation between different tables. They also enable you to select data with relation to data in another table.

The various types are:

INNER JOINs: Blank rows are left in the middle while more than equal to two tables are joined.

OUTER JOINs: Divided into Left Outer Join and Right Outer Join. Blank rows are left at the specified side by joining tables in other side.
Other joins are CROSS JOINs, NATURAL JOINs, EQUI JOIN and NON-EQUI JOIN.

Storage and access of data from the central location in ORDER to take some strategic decision is called Data WAREHOUSING. Enterprise MANAGEMENT is used for managing the information whose FRAMEWORK is known as Data Warehousing.

Storage and access of data from the central location in order to take some strategic decision is called Data Warehousing. Enterprise management is used for managing the information whose framework is known as Data Warehousing.

A ‘CORRELATED subquery’ is a sort of SUB query but correlated subquery is reliant on another query for a value that is RETURNED. In CASE of execution, the sub query is executed first and then the correlated query.

A ‘correlated subquery’ is a sort of sub query but correlated subquery is reliant on another query for a value that is returned. In case of execution, the sub query is executed first and then the correlated query.

Restrictions that are applied are:

• Only the CURRENT database can have views.
• You are not liable to change any computed value in any PARTICULAR VIEW.
• Integrity constants decide the functionality of INSERT and DELETE.
• Full-text index definitions cannot be applied.
• Temporary views cannot be created.
• Temporary tables cannot CONTAIN views.
• No ASSOCIATION with DEFAULT definitions.
• Triggers such as INSTEAD OF is associated with views.

Restrictions that are applied are:

SCALAR function is depended on the argument given and RETURNS SOLE VALUE.

Scalar function is depended on the argument given and returns sole value.

Functions which operate against a collection of values and returning single VALUE is CALLED AGGREGATE functions.

Functions which operate against a collection of values and returning single value is called aggregate functions.

Both having B-tree structure, non-CLUSTERED INDEX has DATA POINTERS enabling ONE table many non-clustered indexes while clustered index is distinct for every table.

Both having B-tree structure, non-clustered index has data pointers enabling one table many non-clustered indexes while clustered index is distinct for every table.

Group-clause USES aggregate VALUES to be DERIVED by collecting SIMILAR DATA.

Group-clause uses aggregate values to be derived by collecting similar data.

A QUERY CONTAINED by a query is CALLED Sub-query.

A query contained by a query is called Sub-query.

They are:

DYNAMIC: it reflects changes while scrolling.

Static: doesn’t reflect changes while scrolling and works on recording of snapshot.

Keyset: data MODIFICATION WITHOUT reflection of new data is SEEN.

They are:

Dynamic: it reflects changes while scrolling.

Static: doesn’t reflect changes while scrolling and works on recording of snapshot.

Keyset: data modification without reflection of new data is seen.

A database object which HELPS in manipulating DATA row by row representing a result set is called CURSOR.

A database object which helps in manipulating data row by row representing a result set is called cursor.

FULL recordings of two TABLES is UNION All operator.A distinct recording of two tables is Union.

Full recordings of two tables is Union All operator.A distinct recording of two tables is Union.

CREATE: Create is used in the CREATE TABLE statement.
SYNTAX is:  CREATE TABLE [COLUMN name] ( [column DEFINITIONS] ) [ table PARAMETERS]

ALTER: It helps in modification of an existing object of database.
Syntax is: ALTER objecttype objectname parameters.

DROP: It destroys an existing database, INDEX, table or view.
Syntax is: DROP objecttype objectname.

CREATE: Create is used in the CREATE TABLE statement.
Syntax is:  CREATE TABLE [column name] ( [column definitions] ) [ table parameters]

ALTER: It helps in modification of an existing object of database.
Syntax is: ALTER objecttype objectname parameters.

DROP: It destroys an existing database, index, table or view.
Syntax is: DROP objecttype objectname.

Managing properties and ATTRIBUTES of database is called Data DEFINITION Language(DDL).

Manipulating data in a database such as inserting, updating, DELETING is defined as Data Manipulation Language. (DML)

Managing properties and attributes of database is called Data Definition Language(DDL).

Manipulating data in a database such as inserting, updating, deleting is defined as Data Manipulation Language. (DML)

Boosting up database performance, ADDING of REDUNDANT DATA which in turn HELPS rid of complex data is called denormalization.

Boosting up database performance, adding of redundant data which in turn helps rid of complex data is called denormalization.

Advantages of normalizing database are:

• No duplicate entries
• Saves storage SPACE
• Boasts the QUERY PERFORMANCES.

Advantages of normalizing database are:

ORGANIZED data void of inconsistent dependency and redundancy within a database is CALLED NORMALIZATION.

Organized data void of inconsistent dependency and redundancy within a database is called normalization.

The various relationships of DATABASE are:

• One-to-one: Single table having DRAWN relationship with another table having similar KIND of columns.
• One-to-many: Two tables having primary and foreign key relation.
• Many-to-many: JUNCTION table having many tables RELATED to many tables.

The various relationships of database are:

A data model determining fundamentally how data can be STORED, manipulated and organised and the structure of the DATABASE LOGICALLY is CALLED database model.

A data model determining fundamentally how data can be stored, manipulated and organised and the structure of the database logically is called database model.

As special-purpose LANGUAGES, they have:

• Data DEFINITION language
• Data MANIPULATION language
• Query language

As special-purpose languages, they have:

A database language may also INCORPORATE features like:

• DBMS-specific Configuration and management of storage ENGINE. 
• Computations to modification of query RESULTS by computations, like summing, counting, averaging, grouping, SORTING and cross-referencing Constraint enforcement Application PROGRAMMING Interface.

A database language may also incorporate features like:

The development of database TECHNOLOGY is DIVIDED into:

• Structure or DATA MODEL
• Navigational model
• SQL/ relational model

The development of database technology is divided into:

A database is a LOGICALLY coherent collection of data with some inherent meaning, REPRESENTING some aspect of REAL world and which is designed, built and populated with data for a specific purpose.

A database is a logically coherent collection of data with some inherent meaning, representing some aspect of real world and which is designed, built and populated with data for a specific purpose.

There are two Integrity rules.

Entity Integrity: States that "PRIMARY KEY cannot have NULL value".

REFERENTIAL Integrity: States that "Foreign Key can be either a NULL value or should be Primary Key value of other RELATION.

There are two Integrity rules.

Entity Integrity: States that "Primary key cannot have NULL value".

Referential Integrity: States that "Foreign Key can be either a NULL value or should be Primary Key value of other relation.

The standard SQL Lite commands interact with relational DATABASES are similar to SQL. They are

• SELECT
• CREATE
• INSERT
• UPDATE
• DROP
• DELETE

Based on their operational nature these commands can be classified.

The standard SQL Lite commands interact with relational databases are similar to SQL. They are

Based on their operational nature these commands can be classified.

• USING transactions we can group all SQL COMMANDS into a SINGLE unit.
• The transaction begins with some task and finishes only when all tasks within it are over.
• The transaction gets over SUCCESSFULLY only when all commands in it are successfully over. Even if one command fails, the whole transaction fails.
• The BEGIN TRANSACTION, ROLLBACK TRANSACTION, and COMMIT TRANSACTION statements are used to work with transactions.
• A group of tasks starts with the begin statement.
• In case of any problem, the rollback command is executed to abort the transaction.
• If all the tasks run successfully, all commands are executed through commit statement.

SQL LITE is a mostly ACID compliant RELATIONAL database MANAGEMENT system CONTAINED in a RELATIVELY small C PROGRAMMING library.

SQL LITE is a mostly ACID compliant relational database management system contained in a relatively small C programming library.

Boolean VALUES in SQL lite are stored as integers 0 (false) and 1 (TRUE). SQL Lite does not have a separate Boolean storage class.

Boolean values in SQL lite are stored as integers 0 (false) and 1 (true). SQL Lite does not have a separate Boolean storage class.

• When the processing of large data is done, this command is used.
• Whenever large number of deletions, modification or copy TAKES place into the TABLES, the indexes NEED to be updated to TAKE care of these changes. UPDATE_STATISTICS performs this JOB.

The SQLITE group by clause is used in COLLABORATION with the SELECT statement to ARRANGE identical DATA into GROUPS.

The SQLITE group by clause is used in collaboration with the SELECT statement to arrange identical data into groups.

• Physical level: The LOWEST level of abstraction describes how data are STORED.
• LOGICAL level: The NEXT higher level of abstraction, describes what data are stored in database and what RELATIONSHIP among those data.
• View level: The highest level of abstraction describes only part of entire database.