This article provides a high-level overview of IMS database concepts, terminology, and database design considerations. It covers the following topics:

Overview
The term database means a collection of related data organized in a way that can be processed by application programs. A database management system (DBMS) consists of a set of licensed programs that define and maintain the structure of the database and provide support for certain types of application programs. The types of database structures are network, relational, and hierarchical. This manual presents information on IMS, a hierarchical database management system from IBM*.

The IMS software environment can be divided into five main parts:
+ database
+ Data Language I (DL/I)
+ DL/I control blocks
+ data communications component (IMS TM)
+ application programs


Figure 1-1 shows the relationships of the IMS components. We discuss each of these components in greater detail in this and subsequent chapters.

IMS Database
Before the development of DBMSs, data was stored in individual files, or as flat files. With this system, each file was stored in a separate data set in sequential or indexed format. To retrieve data from the file, an application had to open the file and read through it to the location of the desired data. If the data was scattered through a large number of files, data access required a lot of opening and closing of files, creating additional I/O and processing overhead. To reduce the number of files accessed by an application, programmers often stored the same data in many files. This practice created redundant data and the related problems of ensuring update consistency across multiple files. To ensure data consistency, special cross-file update programs had to be scheduled following the original file update.

The concept of a database system resolved many data integrity and data duplication issues encountered in a file system. A database stores the data only once in one place and makes it available to all application programs and users. At the same time, databases provide security by limiting access to data. The user's ability to read, write, update, insert, or delete data can be restricted. Data can also be backed up and recovered more easily in a single database than in a collection of flat files.

Database structures offer multiple strategies for data retrieval. Application programs can retrieve data sequentially or (with certain access methods) go directly to the desired data, reducing I/O and speeding data retrieval. Finally, an update performed on part of the database is immediately available to other applications. Because the data exists in only one place, data integrity is more easily ensured.

The IMS database management system as it exists today represents the evolution of the hierarchical database over many years of development and improvement. IMS is in use at a large number of business and government installations throughout the world. IMS is recognized for providing excellent performance for a wide variety of applications and for performing well with databases of moderate to very large volumes of data and transactions.

DL/I
Because they are implemented and accessed through use of the Data Language I (DL/I), IMS databases are sometimes referred to as DL/I databases. DL/I is a command-level language, not a database management system. DL/I is used in batch and online programs to access data stored in databases. Application programs use DL/I calls to request data. DL/I then uses system access methods, such as Virtual Storage Access Method (VSAM), to handle the physical transfer of data to and from the database.

IMS databases are often referred to by the access method they are designed for, such as HDAM, PHDAM, HISAM, HIDAM, and PHIDAM. IMS makes provisions for nine types of access methods, and you can design a database for any one of them. We discuss each of them in greater detail in Chapter 2, "IMS Structures and Functions." The point to remember is that they are all IMS databases, even though they are referred to by access type.

Control Blocks
When you create an IMS database, you must define the database structure and how the data can be accessed and used by application programs. These specifications are defined within the parameters provided in two control blocks, also called DL/I control blocks:
+ database description (DBD)
+ program specification block (PSB)


In general, the DBD describes the physical structure of the database, and the PSB describes the database as it will be seen by a particular application program. The PSB tells the application which parts of the database it can access and the functions it can perform on the data.

Information from the DBD and PSB is merged into a third control block, the application control block (ACB). The ACB is required for online processing but is optional for batch processing.

Data Communications
The IMS Transaction Manager (IMS TM) is a separate set of licensed programs that provide access to the database in an online, real-time environment. Without the TM component, you would be able to process data in the IMS database in a batch mode only. With the IMS TM component, you can access the data and can perform update, delete, and insert functions online. As Figure 1-1 shows, the IMS TM component provides the online communication between the user and DL/I, which, in turn, communicates with the application programs and the operating system to access and process data stored in the database.

Application Programs
The data in a database is of no practical use to you if it sits in the database untouched. Its value comes in its use by application programs in the performance of business or organizational functions. With IMS databases, application programs use DL/I calls embedded in the host language to access the database. IMS supports batch and online application programs. IMS supports programs written in ADA, assembler, C, COBOL, PL/I, VS PASCAL, and REXX.

Hierarchical versus Relational Databases

There are several types of database management systems, categorized generally by how they logically store and retrieve data. The two most common types in use today are relational and hierarchical. Each type has its advantages and disadvantages, and in many organizations both types are used. Whether you choose a relational or hierarchical database management system depends largely on how you intend to use the data being stored.

Relational Database
In a relational database, data is stored in a table made up of rows and columns. A separate table is created for logically related data, and a relational database may consist of hundreds or thousands of tables.

Within a table, each row is a unique entity (or record) and each column is an attribute common to the entities being stored. In the example database described in Table 1-1 on page 1-9, Course No. has been selected as the key for each row. It was chosen because each course number is unique and will be listed only once in the table. Because it is unique for each row, it is chosen as the key field for that row. For each row, a series of columns describe the attributes of each course. The columns include data on title, description, instructor, and department, some of which may not be unique to the course. An instructor, for instance, might teach more than one course, and a department may have any number of courses. It is important early in design of a database to determine what will be the unique, or key, data element. Hierarchical Databases

Now let's look at the same data stored in a hierarchical format. This time the data is arranged logically in a top-down format. In a hierarchical database, data is grouped in records, which are subdivided into a series of segments. In the example Department database on Figure 1-2 on page 1-8, a record consists of the segments Dept, Course, and Enroll.

In a hierarchical database, the structure of the database is designed to reflect logical dependencies-certain data is dependent on the existence of certain other data. Enrollment is dependent on the existence of a course, and, in this case, a course is dependent on the existence of a department. In a hierarchical database, the data relationships are defined. The rules for queries are highly structured. It is these fixed relationships that give IMS extremely fast access to data when compared to a relational database. Speed of access and query flexibility are factors to consider when selecting a DBMS.

Strengths and Weaknesses

Hierarchical and relational systems have their strengths and weaknesses. The relational structure makes it relatively easy to code requests for data. For that reason, relational databases are frequently used for data searches that may be run only once or a few times and then changed. But the query-like nature of the data request often makes the relational database search through an entire table or series of tables and perform logical comparisons before retrieving the data. This makes searches slower and more processing-intensive. In addition, because the row and column structure must be maintained throughout the database, an entry must be made under each column for every row in every table, even if the entry is only a place holder-a null entry. This requirement places additional storage and processing burdens on the relational system.

With the hierarchical structure, data requests or segment search arguments (SSAs) may be more complex to construct. Once written, however, they can be very efficient, allowing direct retrieval of the data requested. The result is an extremely fast database system that can handle huge volumes of data transactions and large numbers of simultaneous users. Likewise, there is no need to enter place holders where data is not being stored. If a segment occurrence isn't needed, it isn't inserted.

The choice of which type of DBMS to use often revolves around how the data will be used and how quickly it should be processed. In large databases containing millions of rows or segments and high rates of access by users, the difference becomes important. A very active database, for example, may experience 50 million updates in a single day. For this reason, many organizations use relational and hierarchical DBMSs to support their data management goals.

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