What Is a Database Schema?

A database schema represents the structure or the organization of data in a database management system.

What Is a Database Schema?

  • A database schema refers to the logical and visual configuration of the entire relational database. The database objects are often grouped and displayed as tables, functions, and relations. A schema describes the organization and storage of data in a database and defines the relationship between various tables. A database schema includes descriptive details of the database that can be depicted through schema diagrams.
  • Database designers create database schemas to help programmers interact with the database efficiently. The process of creating a database is known as data modeling. To design a database schema, you need to gather information and arrange them into tables, rows, and columns. You need to organize the information to make it easier to understand, relate, and use.

  • Database schema design provides a blueprint to develop the architecture of the database, so a massive amount of information can be stored systematically. It also refers to the strategies and best practices involved in constructing a database. Database schema design makes the data much easier to consume, interpret, and retrieve by organizing it into separate entities and determining the relationships between organized entities.

  • Database schema design ensures data has consistent formatting, all entries have a primary key, and important data is not excluded. A database schema can exist as visual or logical, including a set of formulas to govern the database. Developers use these formulas and data definitions to create the database schema.

    The most common types of database schemas are outlined below:

    Hierarchical model: A database schema with tree-like structures with child nodes attached to the root node is hierarchical. This database schema model can store nested data, including family trees.

    Flat model: A flat model organizes data into a single or two-dimensional array-like in a spreadsheet with rows and columns. The model is appropriate for simple data without complex relations that can be arranged in tabular format.

    Relational model: The relational model is similar to a flat model in which data is organized into tables, rows, and columns. However, in this model, you can define relationships between different entities.

    Star schema: A star database schema organizes data into "dimensions" and "facts." Dimensions include descriptive data, while facts have numeric values.

    Snowflake schema: The snowflake database schema is a logical representation of data in a database. The representation of this type of schema is similar to snowflake, where multiple dimensions are attached to a single centralized fact table.

    Network model: A network database schema includes data as multiple nodes connected. This model is used to accomplish specific tasks as it allows complex connections such as many-to-many relationships.
  • Outlined below are a few best practices to make the best use of your database schema.

    • Security: An effective database schema design must focus on data security. Assign roles and responsibilities to each database user, avoid unauthorized access, and use advanced encryption to secure sensitive data such as login credentials, personally identifiable information (PII), and passwords.
    • Name conventions: To make your schema design more effective, you can define appropriate naming conventions in your database. Avoid using complex names, special characters, and reserved words in tables, columns, and field names.
    • Normalization: Normalization helps eliminate redundancy by ensuring independent entities and relationships aren’t grouped in the same table and columns. This improves the integrity of the data and makes it easier for developers to retrieve information. Normalization can also be used to optimize database performance.
    • Documentation: Database schemas are crucial for developers and creating documentations. You must document your database schema design along with instructions, comments, scripts, and more.
    • Physical database schema: The physical database schema represents the physical arrangement of data and how it’s stored in blocks of storage such as files, indices, key-value pairs.
    • Logical database schema: Logical database schema describes the logical representation of data and conveys logical constraints. The data can be described as certain types of data records and is stored as different data structures. However, internal details like data implementation are hidden at this level.
  • Database schemas are cognitive frameworks or concepts designed to organize information systematically. Schemas allow interpreting a vast amount of information quickly. Unorganized databases can be confusing and difficult to maintain and administer. With a clean, efficient, and consistent database schema design, you can make the best use of your organization's data. Relational databases highly depend on database schema design to eliminate data redundancy, prevent data inconsistencies, facilitate data retrieval and analysis, ensure the integrity of the data, and keep it safe from unauthorized access. It’s crucial to organize data into tables and columns with a strong test environment. You need a plan to manage data integrity and update your database and source code.
Featured in this Resource
Like what you see? Try out the products.
Database Performance Analyzer

Monitor and optimize multiple database management system (DBMS) platforms for cloud and on-premises environments.

Email Link To TrialFully functional for 14 days
SolarWinds SQL Sentry

SolarWinds SQL Sentry provides database performance monitoring for only the Microsoft SQL Server and platform.

Email Link To TrialFully functional for 14 days

View More Resources

What is Database Management System (DBMS)?

Database performance management system is designed to help admins more easily troubleshoot and resolve DBMS performance issues by monitoring performance and providing root-cause analysis of your database using multi-dimensional views to answer the who, what, when, where, and why of performance issues.

View IT Glossary

What is SSAS (SQL Server Analysis Services)?

SQL Server Analysis Services (SSAS) is a multidimensional online analytical processing (OLAP) server and an analytics engine used for data mining. It allows IT professionals to break up large volumes of data into more easily analyzed parts. A component of Microsoft SQL Server, it helps enable analysis by organizing data into easily searchable cubes.

View IT Glossary

What is MIB?

MIB is an organized, up-to-date repository of managed objects for identifying and monitoring SNMP network devices.

View IT Glossary

What is CPU usage?

CPU utilization indicates the amount of load handled by individual processor cores to run various programs on a computer.

View IT Glossary

What is a Relational Database?

A relational database allows you to easily find, scan, and sort specific information based on the relationship among the different fields defined within a table.

View IT Glossary

What is Database Concurrency?

Database concurrency is a unique characteristic enabling two or more users to retrieve information from the database at the same time without affecting data integrity.

View IT Glossary