Data Warehouse vs Database: Key Differences Explained

Data management is extremely important for all businesses with data warehouses and databases being two popular solutions, but what are the differences between them and how do you know which is best suited to your organisation?

Learn how they differ from each other and which data management solution is best to incorporate into your strategy.

What is a database?

A database is a system that is used for storing, organising, and managing data. It allows businesses to efficiently add, retrieve, and modify information.

Databases can consist of various data types such as names, addresses, financial records, and more. They are an indispensable tool in both business and technology for the management of extensive datasets.

They can range from basic systems that use table-based data management, to more complex databases enabling robust querying and comprehensive data analysis.

Databases are an efficient way to quickly process large volumes of queries to find the information you need and they support OnLine Transactional Processing (OLTP).

OLTP is a type of data processing that involves handling multiple real-time transactions simultaneously, such as online banking, shopping, order entry, or sending text messages. These transactions are typically economic or financial in nature and are recorded and secured so they can be easily accessed at any time for accounting or reporting needs.

What is a data warehouse?

A data warehouse is a specialised type of database optimised for analysing and reporting large sets of data. It gathers information from multiple sources, including operational databases, and organises it in a way that makes it easier for businesses to perform complex queries and generate reports.

Data warehouses are designed to support decision-making processes by providing a centralised, consolidated view of an organisation's data. They are essential for business intelligence activities, allowing users to identify trends, patterns, and insights that can inform strategic planning and improve performance.

Traditional data warehouses only store historical business data however there are real-time data warehouses (RTDW) that can use live data. This option is ideal for gaining quick insights into your business.

They use OnLine Analytical Processing (OLAP). This is a method of computing that lets users extract and query data easily to analyse it from various perspectives. It's commonly used for trends analysis, financial reporting, sales forecasting, budgeting, and other planning tasks related to business intelligence.

Key differences between a database and a data warehouse

A database holds the present data necessary for running an application, while a data warehouse includes both current and historical data from one or more systems using predefined and fixed schema. The primary aim of a data warehouse is to facilitate data analysis.

Why use a data warehouse?

Data warehouses are an excellent choice when dealing with vast amounts of data and conducting complex queries and analysis. Their structured format helps to simplify data analysis making it more accessible for business analysts and data scientists to use.

There are a range of benefits to using a data warehouse which include:

• Informed decision-making: A unified view of data that is consistent is one of the most effective ways for an organisation to make informed decisions. Key decision makers and those who analyse data have easy access to comprehensive information they can trust. Data warehouses are suited to complex queries and can be used to find insights that would not be possible to identify without it.
• Centralised data for business intelligence: Data warehouses consolidate data from various areas across the business storing it all in a single place providing users across all levels of an organisation access to the information they need. This accessibility allows users to monitor performance, identify opportunities, and optimise operations, regardless of their skill level.
• Data consistency and quality: When managed effectively, a data warehouse can ensure data quality across the business. Multiple data sources should go through a thorough data integration process to make them consistent and accurate. This helps organisations trust the integrity of the data they are using.
• Optimised storage and historical data: Data warehouses are built to handle large volumes of data that can be used for complex analytical operations, separating analytics processing from transactional databases to enhance performance. Holding historical data, this enables businesses to study both long-term and periodic trends to make more accurate forecasting and improve ROI.
• Scalable for future growth: They provide scalability so they can be easily expanded to accomodate growing data storage needs as a business evolves. This scalability ensures the data warehouse can be used as the business grows instead of needing to be fully replaced with a new one.
• Data security: Databases usually come with built-in security features to protect sensitive information. Access controls, encryption, and authentication features help safeguard data from unauthorised access and breaches.

Data warehouses aren't designed to handle transaction and concurrency access needs that applications have. A separate database will be needed to support your daily operational needs if you choose to have a data warehouse.

Why use a database?

Databases are ideal for day-to-day business operations. They simplify the data management process allowing users to store data in a structured form and access it whenever they need. Using a database offers several advantages for organisations:

• Centralised data repository: A database can help businesses easily manage their growing data in one central and secure location. If data is stored in different places, it can end up being duplicated however by using one centralised location, this is able to eliminate data redundancy.
• Data consistency and quality: Centralised data is structured which helps to prevent duplication making it easier for analysis. They also have built-in safeguards to protect data from being lost making them extremely reliable.
• Easy access: Storing data in your database makes it quick and easy to access for day-to-day operations. You can set up different parts of the database to restrict access to specific users, ensuring confidentiality. Databases are an efficient way to securely share information across different locations and departments.
• Allow multiple users: Databases enable multiple users to collaborate and share information supporting daily business operations. They ensure the data remains consistent even when multiple people are accessing the data at the same time. This prevents issues arising if different users make changes at the same time.
• Data security: Databases allow you to set user permissions so you can make sure certain data is kept confidential. Users can have access to the data they need to perform their job without giving access to private data. This reduces the risk of data leaks, misuse of company data or identity theft.
• Prevents data loss: Databases automatically backup data so it can be restored if there are any server crashes. Data can easily be recovered making it a foolproof way to protect it.

Best practices for databases & data warehouses

When using a database or data warehouse, there are some best practices you should follow which include:

• Keep data up to date: Ensure data is recent by using data pipelines or an automated data refresh process that updates it in real-time or near enough.
• Employ an appropriate data model: Organise and structure data using a suitable data model that aligns with your specific data needs and usage patterns.
• Optimise data processing: Maximise query performance by optimising data to its fullest extent. Using techniques such as data compression, OLAP, or OLTP can enhance data processing speed.
• Prioritise data security: Set up robust data security policies and encrypt data whenever possible to safeguard sensitive information. Set appropriate data access permissions for users and follow all data privacy regulations correctly.
• Monitor data usage: Keep track of data usage metrics to gain insights into how data is being used. This information can help you improve data pipelines and processes so your team can get the most out of data when performing analyses.

Data warehouses & databases vs. data marts & data lakes

Data warehouses and databases are not the only data storage systems available to improve the data management process. Here are some alternative options to consider:

Data marts

A data mart is a simple form of a data warehouse which focuses on a specific area of a business such as sales or marketing. They typically gather data from a smaller number of sources compared to data warehouses. They may even draw data from a central data warehouse. Data marts can incorporate various types of data, including external data and internal data, to provide a more comprehensive view for specific business needs.

Data lakes

A data lake is a centralised storage system built to handle large quantities of raw, unprocessed data in its original form. Unlike traditional data warehouses, data lakes do not need predefined schemas, data transformations, or visualisations before being processed. This flexibility enables organisations to gather structured, semi-structured, and unstructured data from a wide variety of sources, creating a comprehensive repository for data analysis and exploration that is highly flexible.

Which is right for me?

They are both excellent options for storing data however which one is the best option for you depends on exactly what your needs are. Every organisation will need a database if they want to use it to support daily operations. A data warehouse only holds historical data so there is no real-time data.

A database is primarily designed for transactional processing, managing day-to-day operations, and ensuring data integrity within an organisation. On the other hand, a data warehouse is tailored for analytical processing. They store large amounts of historical data that can be thoroughly analysed to generate business intelligence to help make informed decisions.

Choosing between a data warehouse and a database depends on the specific requirements and objectives of the organisation. For businesses focused on real-time transactional processing and maintaining data integrity, a database is the preferred option. However, for organisations prioritising data analysis, business intelligence, and decision-making based on historical data, a data warehouse is the better option.

Conclusion

Both data warehouses and databases play crucial roles in modern data management strategies. By leveraging the strengths of each, businesses can establish robust data infrastructure that supports their operational and analytical needs, driving innovation and competitiveness in today's data-driven landscape.

Our Data Management Solutions are fully bespoke and designed to help you get the most out of your data. Our services will help you monitor, report and make informed decisions faster ensuring you stay ahead of the competition.

Get in touch with our team to see how we can help you with your data management needs.