The current business world thrives on data and companies are spending significantly to build advanced Database Management Systems to achieve this goal. However, the process of designing an efficient database system requires multiple phases and one of the most important phases is designing the Physical Model for the database schema. This process converts the logical design for a database schema and creates a working model for processing vast datasets.
This article will introduce you to the Physical Design Database process and elaborate on its key features. It will also explain the importance of this process and discuss the whole Database Development Cycle. Furthermore, it will list the key elements required to build an optimal Physical Design Database. Read along to learn more about this process and the challenges involved!
Table of Contents
What is a Physical Design Database?
The act of generating a data structure (physical) from a data model to implement a Database Management System DBMS is called Physical Database Design. This transformation occurs in multiple steps starting from a business model which finally expands to become a fully attributed model. The model is further modified to work as the data structure and this marks the completion of the Physical Design Database process.
The Physical Design Database showcases various attributes of your project or developing application. For instance, a good database design specifies every table and column, holds foreign keys to recognize the relationships between 2 tables, etc. Such aspects differentiate the Physical Data Model from the Logical Data Model. The logical model is the blueprint on which your Physical Design Database is built.
Key Features of Physical Design Database & Implementation
The following features work together to provide you with the benefit of using the Physical Design Database for your RDBMS:
- Tablespaces: Tablespaces represent the actual storage where a database object saves its data. In your Physical Design, all Tablespaces must be distinct and no overlapping should exist. This implies, that tables & their indexes must reside separately and similarly large and small tables should have their distinct location.
- Partitions: Partitioning is the task of creating smaller tables to divide the data stored in larger tables in a database. This facilitates higher query processing performance as it is easier to manage the smaller tables.
- Indexes: Indexing is a critical aspect of Data Warehousing and they are easy to work with due to their resemblance to OLTP indexes. However, one must be careful while managing the bitmap indexes in a physical design database as they can affect the overall stability of the physical design.
- Constraints: Constraints act as the boundaries under which you can perform the Physical Design Database process. Moreover, due to a difference in the number of data sources, both OLTP and Data Warehouses allow you to work under different constraints. Therefore you should design your Physical Model accordingly.
Importance & Relevance of Physical Design Database
The physical design of your database is highly relevant as its right implementation is necessary to make the logical blueprint of the database system work. The physical design can optimize the query processing performance while simultaneously maintaining Data Integrity by preventing data redundancies. This optimal setup will also allow the database users to manage and access their data with more ease.
The Physical Design Database process allows you to convert the information and ideas collected during the logical planning phase into a detailed description of the physical model for your database. The difference between logical and physical modes is shown in the below image.
The Physical Design Database is important because it showcases the exact implementation of your data model in the desired database. This representation includes all tables with the required column name, data type, constraints, primary & foreign keys, etc. Furthermore, the physical design allows you to translate design schemas into real database structures and customize them to suit your business needs.
What is the Database Life Cycle?
The database life cycle contains all the fundamental steps required for designing a logical database using Conceptual Modelling, and further devising a physical database that contains proper indexing, partitioning, clustering, and works with optimal real-time performance. Once these 2 models are completed, the life cycle moves on to work on database implementation and finally, its maintenance. The 4 steps of the Database Life Cycle are as follows:
1. Requirements Analysis: This step is about gathering the information required to start planning the database design. The analysis is carried out by interviewing the developers and users of database systems via surveys, formal meetings, etc. The results of this analysis are converted into specifications which showcase the data relationships and expected output of database software.
2. Logical Database Design: This step utilises the specifications generated during the analysis phase and builds the database system’s conceptual model (Logical Design). This phase leverages Unified Modeling Language (UML) and (ER) modelling to capture the user’s expectations in terms of data entities and their relationships. Ultimately a huge schema is developed incorporating all the data tables and their connections with each other in a normalized form.
3. Physical Database Design: Once the SQL tables are ready in a normalized form, the logical schema is transformed into a physical database design. This phase applies indexing, partitioning, and clustering of data to store the database tables in a way that facilitates easy access for users. The goal of this Physical Design Database process is to ensure maximum performance of your database across all the applications that rely on it.
4. Database implementation & Monitoring: After the physical design is complete you can use the Data Definition Language (DDL) to create new tables and add data to them. Furthermore, you can deploy Data Manipulation Language (DML) queries and modify & manipulate data according to your needs,
Now, in case certain schema level changes are required for the DBMS, you need to go again for requirement analysis and work your way up to logical and physical designing in the Data Cycle,
Key Elements & Considerations of Physical Design Database
When designing the physical structure of your database system, keep the following key considerations in mind:
An index in a database is a means of stepping up the data retrieval speed for user queries. The SQL query processing engine knows where to search for a particular result when the stored data is indexed. This is why indexing your data tables is a must while implementing Physical Design Database.
You can easily specify indexes in your database management systems using the following SQL command:
CREATE UNIQUE INDEX supplierNum ON supplier(sum);
This will generate a unique index for a key. A unique index represents a tabular data structure whose entries are in the form of attribute-value pairs which are accessed using certain printers. Moreover, such type of ordered index works on a key attribute whose values are stored either in the ASCII form or strictly as alphabets.
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In a Physical Design Database, partitioning is useful to reduce the workload on any single hardware component. FOr instance, you can decrease the burden of your main disk by partitioning its data into several smaller disks. This will balance the system’s load and will allow you to avoid bottlenecks.
The most common form of partitioning is the Range Partitioning which stores data attribute values by sorting them according to a certain range. Afterwards, records present under a given range are stored in a specific disk to facilitate independent processing for that partition.
Database Clustering is the task of unifying multiple instances that connect to a single database. This is beneficial in situations where a single server or instance is not sufficient to manage the total quantity of data requests generated. Database Clustering and SQL Clustering are some of the most popular ways to combine data from different instances.
The major advantage of database clustering is its load balancing capability for a server. Furthermore, clustering promotes high data availability and better monitoring.
Challenges of Physical Design Database
The process of Physical Design Database faces the following challenges:
- The major challenge that occurs during the physical database design is deciding the storage format of every attribute. Moreover, selecting the correct grouping attribute grouping to form physical records and choosing accurate structures for connecting files for efficient data retrieval also act as bottlenecks in this endeavour.
- When working on Physical Design Database, you must aim to minimize the response time for user-system interactions. Moreover, the chosen storage format should also be optimal in terms of speed & space required during data processing. This implies, that your chosen storage format must work to minimize the storage space and enhance data integrity.
- The physical design of your database also requires considerations related to the grouping of attributes during the logical to physical data model transition. records. Moreover, you must monitor data volumes and statistics related to user consumption.
The article introduced you to creating the Physical Design of a database and discussed its key features. It then explained the importance of the Physical Design Database and emphasis on the 3 key elements required to optimize it. The article also discussed the Database Life Cycle and listed the challenges which you may face in this endeavour.
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