In today’s fast-moving technology environment, the most critical aspect is the data or information that forms any organisation’s backbone. Database and Data Warehouse are two commonly used systems for managing data.
Although both of them perform the same task of data administration, there is a spring difference between these concepts as they serve different purposes and utilize various technologies in data management.
Key Takeaways
- Databases store and manage current, operational data; data warehouses consolidate historical and analytical data for decision-making.
- Databases support transactional processing (OLTP); data warehouses facilitate analytical processing (OLAP).
- Databases are optimized for quick data retrieval and updates; data warehouses are designed for efficient querying and reporting on large data sets.
Database vs Data Warehouse
The difference between Database and Data Warehouse is that Database is used to record data or information, while Data Warehouse is primarily used for data analysis.
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However, the above is not the only difference. A comparison between both the terms on specific parameters can shed light on subtle aspects:
Comparison Table
| Parameter of Comparison | Database | Data Warehouse |
|---|---|---|
| Meaning | An organized collection of data stored and accessed electronically | The system used for storing, retrieving, managing, reporting and analyzing large amounts of data |
| For what purpose? | For storing data | For analysis of data |
| Procedure used | Data is captured/populated | Data is scrutinized/analyzed |
| Processing method | Online Transactional Processing | Online Analytical Processing |
| Techniques/methods | ER modelling procedures | Data modelling procedures |
| Storing data | Flat Relational Approach technique | Dimensional snowflake method |
| Decision making | Not much used as it only involves storing data | Highly useful as it analyses the data |
| Query types | Simple | Complex |
| Where is it commonly used? | Used in almost all industries, such as banking, finance, healthcare, telecommunication, and aviation; however, users will be limited to storing data, customer records, bills, stock and sales information. | Used in almost all industries, such as banking, finance, telecommunication, and aviation; however, usage will be for analysing information, predicting outcomes, studying patterns or behaviours, and helping overall decision-making. |
What is Database?
A database is usually a massive data collection systematically organized into columns and rows.
In other words, a Database can be considered a collection of information organized and used on a computer/system. The database is the foundation or the starting phase of the building or analysis of data.
A database usually contains data or information organized in columns, rows, and tables. The data can be periodically updated or indexed to make it easily accessible or retrieved.
Organizations utilize Database management systems (DBMS) to store customer, inventory, finance, sales, and human resources information.
The database offers multiple advantages, such as easy search and retrieval, security features, data sharing, various views, support for the multi-user framework, and multi-transaction processing.
Most importantly, Database follows the ACID compliance (Atomicity, Consistency, Isolation, and Durability) model, which avoids duplicate processing and other errors.
The database is not free from the cons. Some of the features of a Database that make it not a worthwhile option for many include the cost of implementation, which is relatively high for large amounts of data, the complexity of some Databases, which again increases the cost of understanding and training, and problems with compatibility with other systems.
The database may not be able to undertake complex operations/calculations and analysis of data, and hence decisions cannot be taken based on the data stored in the Database.
What is Data Warehouse?
Data Warehouse is a system or method used for analyzing and managing vast amounts of data.
Data Warehouse is an information or documentation set up to store and analyze complex and large volumes of historical and current data.
Data Warehouse garners data from multiple sources, analyses the same and helps in generating reports for management purposes. The data to be analyzed can be from single or multiple applications or sources.
Data Warehouse uses complex queries to generate customized analytical reports.
Data Warehouse is primarily used for reporting, condensing, analyzing, and integrating data for decision-making. Data Warehouse includes advanced methodologies for quick search, advanced filters and accurate analysis.
Data Warehouse can be considered a single version of truth (SVOT) for an organization regarding analysis and decision-making. Data stored in a Data Warehouse is non-volatile, meaning it will not be erased when new data is added.
Data Warehouse is not free from shortcomings. Some of the common problems of Data Warehouse include high costs associated with implementation, maintenance, and training as it is complicated.
Data Warehouse involves too much time consuming for certain activities such as loading, and extracting the data, adding new data, or updating existing data.
Main Differences Between Database and Data Warehouse
- A database is utilized for data storage. Data Warehouse is used for data scrutinizing and analysis.
- Database utilizes the Online Transactional Processing (OLTP) method for storing data. Data Warehouse utilizes the Online Analytical Processing (OAP) method to analyse data.
- The database is commonly used in performing operational aspects of the business. Data Warehouse touches on the deeper aspects of business, i.e. analyzing the data for decision-making.
- Database usage may be restricted to only a single application. Data Warehouse usage can involve multiple applications.
- The database will use simple query types. Data Warehouse involves complex queries due to the analysis requirements.
- The database will commonly have data which is always new. Data Warehouse may not always have up-to-date data.
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Sandeep Bhandari holds a Bachelor of Engineering in Computers from Thapar University (2006). He has 20 years of experience in the technology field. He has a keen interest in various technical fields, including database systems, computer networks, and programming. You can read more about him on his bio page.
