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Object oriented database provides storage for the object. The database provides, a query language, transaction, indexing over many servers. Object oriented databases which are also known as (ODBMS) object database management systems. Object database(ODMBS)stores database as real numbers, strings and integers. These are used in object languages as well, etc java, C++ and many others. The following are consider the objects. In some database we can find different extra tools like visual schema, debuggers etc.
Data defines characteristics of an object. Data can be a referred to a complex number or in the other hand it can be a real, integer and a string. Hence object contains data and executable code. Data and methods are defined by classes. A class in object oriented database create an object and can be used to recreate the database that does not store properly. As we know that methods are not storing in the database that's why classes are used to recreate database.
Relational Databases Comparison
Data is store in two dimensional tables. As these tables are normalized and in this case data is not repeated. In all tables columns primary key is used to identify the columns. Once the column is identified the data can be changed or obtained from the associated columns. Objects that we need to put in a database must be in term of a integer, string or a real number data. For example of the airplane. The wings of the airplane may be in a table with rows and columns to describe the dimension and characteristics. And all others part of the airplane maybe placed in the different tables and so on.
In traditional database, application manipulates the data and that data is called persistence (permanent storage device) and in the case of object database application manipulate transient data and as well persisted data.
Object Databases uses age timing.
The object databases must be used there is complex data relationship or a complex data. Its also include many to many relationship. The object data should not be used if there is few table and large transactional data.
Different kinds object databases.
Computer applications like CAS and CAM.
Project that change by time. (Object)
Comparison of Object Database over RDBMS
Reducing the number of paging
It is easy to navigate.
Concurrency control is better than RDBMS.
Its data model bases on reality.
Good for distributed architectures.
In Object oriented application less code is required.
Disadvantages of object oriented database compared to RDBMS
Efficiency is low when data and relationship are simple.
Relational tables are very simple.
Late binding causes low access speed.
More user tools (RDBMS.)
(ODMG) that stands for Object Data Management Group
(ODS) that stands for Object Database Standard
(OQL) that stands for Object Query Language
How Data is Store in the database.
The objects are store by two different methods in database techniques. All the object is defined a subclass of a base class and has a unique ID, using inheritance to determine attributes. To storage and management virtual memory mapping is used. Data transfer is done in two ways either per object basis or per page basis
Very Large Database
Recently modern enterprises are running critical databases. These databases are very large in gigabytes and sometimes in terabytes of data. Enterprise is changed by the support and maintenance of (VLDA) data. It must invent some methods from in it to overcome the changes.
There are few topics of very large database portioning, component of data strategy which are listed below.
Introduction to Portioning
Very Large Database and Portioning
Foundation for the lifecycle management (for portioning)
Portioning for every large database
Introduction to portioning
Portioning addresses key support very large tables and also for the indexing. After that you can easily decompose the tables and indexing into small pieces and which are managed very easily. These more manageable pieces are called portion of data. These are converted into application that can be seen in the original condition. But SQL query and DML statement are easily peritonised without modify theirs tables. When the portioning done , the ddl statement can access the individual portioning without tables and indexing. This is how we can manage easily a large database objects in a nice way. Each portion must has the same logical attributes, like column , data type and so on but on the other hand each portion can have the different attributes like compression, table setting etc.
Portioning is very useful for most of the applications. Especially for those applications which manages the large data. By portioning OLDP system, it improves the manageability and availability and on the other hand data warehouse systems performance and manageability.
Advantages of Portioning
It enables data load, index
It creates and rebuilds data
Backup and recovery of data during the portioning process
Without changing the entire table, the process saves the time duration for the operation
In many cases it also improve the performance of the query and then the result of the query can be taken from the sub data portion instead of the entire table
Mission critical data base are available more likely, portioning maintenance can run the different tables and indexing. You can also run the SELECT command and dml on the suffocated portioning. Partitions increase the performance of the system if there are some problems in the window and you have done portioning then it too easy and take less time window recovery. By doing portioning its easy for the system to run smoothly and it increase the system performance. Partitioning make faster acess in the oracle database system. In any case even the data is starting from 10 GB to 10 TB its improve it by magnitude.
VLDB and portioning
As a very large database has no limit on the size of data it may be smaller in size or larger in size. There are different challenges in the portioning that effect on the portioning and the performance of the database, different factor based on the database portioning by size.Many companies regulate to combine a large data all together in a short time and they store data for longer time period. It is a critical factor to manage data.
Foundation for information lifecycles managements portioning
ILM is a easy and manageable data portioning through its useful life and polices. It is important to store the more data and appropriate data at any point in lifecycle. it compress and store data in the read only form. In oracle it is ideal to store IML. It enable the multiple portioning which are very secure and in less time. It also enable data table to be sotre in different tables. The ILM basics operation are Removing the database and it is faster when we use for portioning.
Portioning for every database
As the portioning is the most necessary and compulsory for the large databases Its benefit is not for only large database, it is for all kind of database, even its size is small or medium. We can do it easily. No matter what size of data is will have the same performance and even in large terabyte.
When we define fuzzy relation then fuzzy relational database can be developed. Some structures are defines by fuzzy. Languages that define structures with fuzzy aspects in structure query language statements fuzzy constrain, fuzzy logic and many more.
Fuzzy Relational Database
In relational database, data is matched by using common characteristic of each data in a data set. The output data is organised and its much easy to understand for the many people. Example data set for the real estate that contains all the transactions, in the real world. It can be grouped easily by every year each transaction time, price and buyer first and last name and many more, the grouping the data in this way is called the Relational Databases, To do this grouping the software that is used is relational database management Relational systems.( RDBMS). The term always refers such kind of software, relational databases are the currently the most choice for storing data like personal information, manufacturing and logistical data.
Fuzzy logic is a kind of many logic valued and it deals with the reasoning that are fluid rather than fixed and exact. As compare with the crisp logic where the binary set values are true and false the fuzzy logic have the truth value 0 and 1, fuzzy logic is extended to deal with the partial truth where the truth value ranges from completely true and completely false. When linguistic variable is used the degree is managed by specific function. By Lotfi Zadeh, fuzzy logic began with 1961 proposal of fuzzy set theory. Up to now fuzzy logic have been applied in many fields of science, like control engineering and artificial intelligence. It is very useful for control engineers.
Fuzzy operators in fuzzy set are defines by fuzzy set theory. Only the problem with this is that may we don't know the proper function for that to solve this issue, IF _ THEN rules are used by fuzzy logic or constructers that are equilvent to this, like fuzzy associated matrix. Rules are shown below in the form of IF is property THEN action, lets have a example of a temperature regulator that use a fan.
IF temperature is too cold Then turn off the fan
IF temperature is cold Then slow down the speed of the fan
IF TEMPERATURE IS NORMAL THEN MANTAIN TEMPERATURE LEVEL
IF temperature IS hot THEN increase the speed of the fan
In the above code there is no else statement because the condition are all working, if there is too cold , cold, hot , normal, in all these conditions the program has to work there is NO condition in the fuzzy logic and have named complement as discussed below
There are few opertetors in fuzzy logic that are AND, OR, and NOT OPERATORS and these operators are defined as minimum , maximum and complement, rescpectly, this method of calling these operators is called Zadeh Operators, and fuzzy variable x and y.
x AND y = minimum (truth(x), truth(y))
x OR y = maximum(truth(x), truth(y))
NOT x = (1 - truth(x))
there are some others operators these are more unique in nature and are called hadges which can be applied. These are genrally used adverbs which are written as very, or somewhat, this modifies the meaning of a set in the help of using methodical formulas
Comparison of Fuzzy logic with Probability:
Fuzzy logic and probability are two different methods. On the other hand the theory of both can be used to represent subjective belief. As fuzzy set theory use the concept of fuzzy membership and probability uses the concept of subjective. This is philosophical , fuzzy and probability measures are also totally different and they are not directly equivalent.
Object oriented database is totally different from the relational database. When you compose xml code and it is hard to get the good performance. Many object oriented databases programmers are puzzled when they get to know that they encounter the object oriented database. From all database user points of view there are two kind of database are very dissimilar. An object database is very simple and the other is catch hidden. Very large database in term of definition can be said that it describe the tables in millions of row and column containing the storage. Decision support systems application are serving large numbers of users. As the lack in the research field of fuzzy database as the other methods have suffered similar fates. I am most agree with that databases are imperfect, like any model artefact. There are no system having potential spread uses in other than manipulating and representing.
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