Collection of data or information organized for rapid search and retrieval, especially by a computer. Databases are structured to facilitate storage, retrieval, modification, and deletion of data in conjunction with various data-processing operations. A database consists of a file or set of files that can be broken down into records, each of which consists of one or more fields. Fields are the basic units of data storage. Users retrieve database information primarily through queries. Using keywords and sorting commands, users can rapidly search, rearrange, group, and select the field in many records to retrieve or create reports on particular aggregates of data according to the rules of the database management system being used.
Information can serve many applications, even those not anticipated at the time the database was created. This is in contrast to traditional methods of data storage that hold a fixed amount of data retrievable in a predetermined format, often duplicating the storage of information in as many files as there are applications. For example, the name and address of the same customer may be in a marketing file, a billing file, and an addressing file. If any one of these applications changes, and the programs that access and use the customer record change, then the customer file must change. In database systems, the customer information is retrievable for each application from a shared file that is not dependent upon the application programs for its structure.
Collection of Data stored on a computer storage medium in a common pool for access on an as-needed basis. The same pool of information can serve many applications, even those not anticipated at the time the database was created. This is in contrast to traditional methods of data storage that hold a fixed amount of data retrievable in a predetermined format, often duplicating the storage of information in as many files as there are applications. For example, the name and address of the same customer may be in a marketing file, a billing file, and an addressing file. If any one of these applications changes, and the programs that access and use the customer record change, then the customer file must change.
Storehouse of related data records independently managed apart from any specific program or information system application. It is then made available to a wide variety of individuals and systems within the organization. In essence, it is an electronic filing cabinet providing a common core of information accessible by a program. An example is a data base of inventory items.
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The database terms used in this manual are defined in Definitions. The network database model, which forms the basis of the RDM Embedded system, is described in The Network Database Model. Other Database Models, describes the hierarchical and relational database models. Advantages of the Combined Model describes the advantages of the network model over the relational database model. Specific elements of an RDM Embedded database are described in the final section.
To use RDM Embedded productively, you need to understand RDM Embedded database concepts. This chapter’s purpose is to provide sufficient information for a database novice to use RDM Embedded effectively. As part of our efforts to familiarize you with database concepts, we have provided a Glossary of database terms at the end of this manual.
The basic unit of information in a database is a field. A field (or data field) is an item of data with attributes such as name, type (for example, a character or an integer), and length. Examples of fields are employee name, date of birth, social security number, inventory item code, and serial number. Other database systems or books may use other terms (such as attribute, entity, or column) for field.
A record is a named collection of related fields, which are stored and accessed as a unit. Other database systems or books may use other terms (such as table or file) for record.
Each occurrence (or instance) of a check record in the database contains a value for each of these fields. The definition of a record (made up by its fields) is called the record type and is similar to C structures.
All occurrences of a particular record type are stored in an operating system file. Files are the primary physical storage units of database organization. A database, therefore, is a collection of related files.
A key is a field through which rapid or sorted access to a record is possible. In the check record, you might define check number as a key field, to allow quick retrieval of a check record occurrence through specification of a check number.
An index is a file containing only keys. It is synonymously referred to as a key file. The index to this manual demonstrates the features of a key file: the individual subject entries in the index are the “keys,” while the page where the subject is discussed is analogous to the associated “records.” You can find the page that discusses a desired subject much more quickly by using the index than by reading through each page. And, because the keys are sorted in the index, you can quickly find a specific key. Key files are similar, except the computer does the sorting and look-ups for you. To maintain its key files, RDM Embedded uses the B-tree method, one of the most efficient techniques for implementing an index.
In a key scan operation, the keys in an index are read in the order they appear. Key scans are used to produce sorted listings of records and for fast search operations requiring inspection of a large number of record occurrences (for example, retrieving all checks entered between two dates).
Data relationships often exist between record types.
To associate a particular budget category with each check record, we add a budget code field to the check record type, forming a relationship between the budget record and the check record. Whenever a check is entered, the related budget record is located via the budget code, and the balance for that budget is updated by the amount specified in the check record.
The schema is the conceptual definition of the content and organization of a database. A schema will include the definitions of all record types, with their fields and keys. The form of the schema used by the DBMS is called the dictionary. In RDM Embedded (and most other DBMSs) a Database Definition Language, or DDL, specifies the schema. An RDM Embedded DDL specification for the checking account database is shown below.
A data model (or database model) is a conceptual representation of inter-record relationships. The relational database model establishes and maintains inter-record relationships through common data fields. For example, in the checking account example a common data field, budget code, establishes the relationship between the budget record and the check record.
Other database models, in particular the network database model, establish inter-record relationships directly, through physical links between the related records, rather than through common data fields. These models are discussed in the following sections. Since RDM Embedded supports both the relational and the network database models, you can combine the features of these models to meet the needs of your particular application.
In the network database model, the relationships between record types are explicitly defined and directly maintained through sets. A set defines a one-to-many relationship between two record types.
Sets are implemented with linked lists of pointers to the record locations of the set members and owners. The result is a network of interconnected records.
In the checking account example discussed earlier, the relationship between the budget and check record types could be specified using a set called transactions, defining a one-to-many relationship between a budget record (owner) and the check records (members) written against a particular budget category. In this case, the bud code field in the check record would not be defined in the check record type, as it is redundant.
In the hierarchical database model (a subset of the network model) a record type is allowed to be a member of only one set. Record types can still, however, own more than one set. The owner is called the parent and the member is called the child.
The relational database model views the database as a set of two-dimensional tables (or relations). The columns (also called attributes) of a table correspond to data fields, and the rows of the table correspond to record occurrences. This tabular view of a database is particularly easy to manipulate with standard relational database operations, which are based on mathematical set theory.
In the relational model, relationships between tables are usually established through common data fields. Recall from the initial checking account example that the relationship between the budget and check records was formed by including in the check record a budget code field to identify the budget category.
The principal distinction between the relational and network models is that in the relational model, relationships are formed through common data fields between the related record types, while in the network model those relationships are defined directly.
Note that it is possible to transform databases from relational to network and from network to relational.
The network model eliminates data redundancy by relating the two record types directly, without requiring the duplicate field and index file. Moreover, the related record is accessed directly with one database read operation, where the relational model forces you to read first an index and then the related record.
For those situations where an index is more efficient, RDM Embedded provides you with that option. With RDM Embedded, network access and indexed access are independent methods, so you can combine them to suit the needs of your particular application. Combining these technologies gives you maximum database design flexibility.
We have already discussed two access methods available in RDM Embedded: indexes and sets. A third method is called sequential access. All three methods can be used together for navigating and searching in a database. Each has its own ways of establishing and changing a position in the database. The methods are nearly orthogonal, meaning that the use of one will not disrupt the use of the others. The one value they share is the current record, which points to the record in the database that has been found most recently. The current record is the default object for many of the RDM Embedded functions. All three access methods set the current record.
The indexed method allows you to find a record occurrence by supplying a key. The key can be an exact match, in which case you are positioned directly on a record, or a near match, which will position you just before the record containing a key value higher in the collating sequence. You can also position yourself to the first or last keys of a given key type, regardless of their values. Once at a position, you can move to the previous or next key in the collating sequence. The keys are maintained and navigated in the order maintained in the index, regardless of the physical order of the records to which they point.
The set method allows you to move through set connections in various directions. You can move from the owner of a set instance to the first or last member of the set. From a set member, you can move to the next or previous member record, or to the owner record. During the navigation of sets, positions are established on a per-set basis: the current owner and current member is indicated for each set type that has been used. If defined, a system record can be used as the entry point into a database. When the database is opened, the system record is the current owner of all sets owned by the system record.
The sequential method allows you to find the first, last, next, or previous physical instance of a given record type. RDM Embedded does not allow the programmer to insert records at specific physical positions in a file. Their insertion is normally at the end of a file, but this is not guaranteed if you are using the delete chain. The sequential method is useful when you are searching all records of a given type, but do not care about the order.
An RDM Embedded database consists of:
A dictionary, which stores information describing the content and organization of the database
Data files, which contain occurrences of one or more record types
Key files, which contain an index for one or more key fields
Vardata files, which contain data belonging to one or more variable length fields
Records contain data fields, key fields, and set linkages (which are transparent to the user). They can be accessed through set navigation (that is, traversing through the linked lists associated with specific sets), through key fields (using a fast look-up of the index), sequentially, or through a combination of all three methods.
RDM Embedded now supports storage of databases in shared memory, instead of files. The database contents have the same logical structure, whether stored in shared memory or in files. Thus the division of the database into data files, key files and vardata files applies to in-memory databases as well as disk-based databases. However, a database “file” may now be stored as multiple shared memory segments instead of being stored as a file in the file system.
The database dictionary, which is normally stored in a file created by ddlp or sddlp, can now be placed in a static structure in the application program, avoiding the need for any files at all in an RDM Embedded application. The system files created by RDM Embedded, the TAF and the LOG files, will then also be stored in shared memory segments instead of files.
A database may also be stored partially in memory and partially on disk. Some database files may be stored on disk while others are stored in memory. Key files, which can always be generated from the data files, could be held in memory and regenerated whenever the application starts.
Database files can also be read from disk when the database is opened and then maintained in shared memory while the application is running. When the database is closed the contents of the shared memory can then either be discarded (database files defined as “read”) or written back to disk (database files defined as “persistent”).
A record type, or table, can now be defined as “circular”. Normally, when a table becomes full, RDM Embedded does not allow further record instances to be inserted until some are deleted. With circular tables, when the table becomes full RDM Embedded will still allow new record instances to be created. The new record instances will overwrite existing ones, starting with the oldest. RDM Embedded does not allow explicit deletion of record instances in a circular table.
The definition of a circular table includes a size limit. This provides a useful way of allocating a fixed amount of storage space for storing the most recent instances of a particular record type. For example, this may be useful in storing event data that is being generated rapidly, where only the most recent data is relevant. Circular tables remove the risk that incoming data may fail to be stored due to lack of space, while avoiding the need for the application to delete obsolete data.
A database is an organized collection of information. Common examples of a database would be a telephone book, mailing list, recipe book, or a check book.
The term database is a little different in Access. An Access database refers to a set of data related to a specific purpose or topic, along with the tools needed to utilize and manipulate that data, such as sorting, extracting, or summarizing.
The first term to become familiar with is a Table. An Access table is a list of related information presented in a column/row format.
A table is broken down into additional components such as a row in a table. Each row is referred to as a Record. So if you look up your information in a telephone book you are reviewing your record.
Each column in a table is a category of information referred to as a Field. In a telephone book the column of phone numbers would be considered the Phone Number field.
One item of data, such as a single phone number, is called a Data Value.
Prior to understanding the concept of a Relational Database you should first understand the concept of a Flat File Database. A spreadsheet would be considered a Flat File database.
Another key piece to the relational database concept is each table contains a field, or a combination of fields, in which the data value uniquely identifies the record and Access will ensure that the data values remain unique to each record. This field is referred to as the Primary Key. A Customer Id field would be added to the Customers table and Book Id would be added to Book Inventory table
If each customer is assigned a unique value-their Customer Id-which is then referenced when placing an order. The same would be true for Book Inventory. Each Book is assigned a unique value that is referenced in the Orders table when a book is purchased
Thus the tables are related to each other by a common field.
A table that contains the “parent” or “primary” information can be linked to the appropriate row(s) in a table that contains “child” or “related” information based on common key field of the two tables.
Each relationship will have a Primary (parent) table and a Related (child) table as previously described.
An easy way to determine the Primary table in the relationship is to note the Primary key. Typically the Primary table is the table that holds the Primary key field in the relationship.
In the above image, the Customers table is the Primary table and the Orders table would be the Related table.
How each table is related to each other is another key concept in a relational database.
There are two main types of Relationships: One-to-One and One-to-Many. There is a third relationship type called a Many-to-Many relationship, but I’ll cover that type of relationship in a future article.
A one-to-one relationship exists when the primary record will have only one related record. Another determining factor is both fields used the relationship are Primary Key fields
A one-to-many relationship is the most common type of relationship. A one-to-many relationship exists when the primary record can have many related records
A dbms collection of computer programs that allow storage, modification, and extraction of information from a database. There are many different types of DBMS ranging from small systems that run on personal computers to huge systems that run on mainframes. Examples– Computerized library systems, automated teller machines, flight reservation systems, computerized parts inventory systems.
SQL is an acronym for Structured Query Language . It is the language in which, the client sends the request to the database for data Eg. Select name, address From emp Where city = ‘NOIDA’
Development of a data warehouse includes development of systems to extract data from operating systems plus installation of a warehouse database system that provides managers flexible access to the data
Data mining is a class of database applications that look for hidden patterns in a group of data that can be used to predict future behavior
Data modeling is the analysis of data objects and their relationships to other data objects. Data modeling is often the first step in database design and object-oriented programming as the designers first create a conceptual model of how data items relate to each other. Data modeling involves a progression from conceptual model to logical model to physical schema.