Data Warehouse vs Database
The data warehouse is a system particularly used in data analysis and reporting to find its most important utility in business intelligence. Data warehouse as the name suggests is a concept of a data repository for multiple sources and involved in storage and analysis of both current and legacy data which extensively used in generating analytical reports. The data warehouse is a crucial component of ETL technologies (Extract, Transformation, Load). Typically Data warehouse is composed of staging, integration layers, however, there are other layers as well like access layers. These layers houses are the key functions involved in the data analytics process. In this topic, we are going to learn about Data Warehouse vs Database and their differences. So let us try to understand the difference in the layers functionalities:-
- Staging layer:- This layer primarily works as a data repository for data arriving from various sources and it in turns act as a source for the warehouse layers.
- Integration layer:- The integration layer is involved in the integration of the data received from various sources post the transformation of the same using transformation function.
- Access layer: – This layer is mainly involved in the Load content of EL and enables the user to access the transformed layer.
A database is referred to an organized collection of data, It is generally referred to a set of related data. So in general convention, we can define a database as an integrated collection of relatable information such that it is available for the general reference of the users over a network. A Database is composed of entities along with its attributes.
The features of the entities are referred to as attributes. The primary advantage of the database is that it makes data management easier as it is systematically organized for reference with proper mapping to distinguish among the features.
There are four major types of database namely
- Hierarchical database
- Network database
- Relational database
- Object-oriented database
Let us check on the details for above in details
- Hierarchical database:- This type of database employs the parent-child relationship, It is designed like a tree with nodes representing records and branches to represent fields e.g. Windows registry used in Windows XP OS is an example of the hierarchical database.
- Network Database:- It is generally used for Many to many relational tables resulting in complex database structures.
- Relational Database:- Defines the dependencies of data in form of relations between them and hence find its most common use in database management systems which organizes the data into tables for determining the interdependent relations and generating trends in data. It does not support many to many relationships and has predefined datatypes that they can support, e.g. MySQL, Oracle, etc.
- Object-oriented Database:- Have originated from the relational database, The objects to be stored as treated as Objects and associated with them are attributes. E.g PostgreSQL.
Data Warehouse vs Database Infographics
Below is the top 6 difference between Data Warehouse vs Database :
- The database is based on OLTP and data warehouse is based on OLAP,
- The database is primarily focused on current data and the normalization process reduces the historical content. However, the data warehouse uses historical data to determine insights on business intelligence.
- Database are time variant in nature and only deals with current data, however, the concept of data analytics using historical data makes the corporate decision-making process easier by providing the trends and behavior of the historical data.
- The data warehouse is better on comparing the reporting, analysis and designed to store data available from different data sources. However, the database is based on carrying out dynamic data transaction processing.
Head to Head comparison (Table Format)
|A Data warehouse uses OLAP( Online Analytical Processing) and thus is able to attend to only a small limited complex query at one time||A database uses OLTP (Online Transaction processing ) to perform CRUD(Create, Read, Update, Delete) operation optimize the data processing efficiency and transactional speed of the database system|
|Data Warehouse also performs fast query processing, however, the number of queries per transaction is smaller to database transactional capacity. Further, as part of its business intelligence capabilities, the data warehouse systems are able to provide summarized insights on trends of data||The database can be used to perform fast query processing, allows multi-access to the single data source, and high transactional efficiency.|
|Data Warehouse uses denormalized data structures as it is beneficial for analytical operations on data.||The database uses Normalized data structure with provisions to reduce redundant data and groups of organized data on the basis of the attributes|
|Time-invariant as data warehousing uses historical data to provide analytical trends and hence has to record both currents as well as the historical data for determining the same||Time-variant: – Database is a time variant in nature as they are typically free from historical data. The historical data is considered as a redundancy scope in Normalization and hence the same is removed post successive commits on the data queries.|
|The data warehouse technique is based on OLAP technology and hence is based on complex queries for data analysis. These complex queries are impacting system performance on the basis of the number of transactions being carried out in the system.||Concurrent user access is the biggest advantage of the database, as the OLTP model for data analytics provides scope for a large number of concurrent users to carry on the data processing and operations at the same time without impacting the system performance|
|There are one too many relationships among the data fields in the data warehouse||There is only one to one relationship between the entity fields, the tables are normalized to provide redundancy free and efficient data.|
Conclusion: Data Warehouse vs Database
Data warehouse vs database uses a table based structure to manage the data and use SQL queries for carrying out the same. However, the purpose of both is entirely different as data warehouse is used in influencing business decisions however the database is used for online transactional processing and data operations. Also, the data type considered is different in both the cases as database uses current data for its operations however the data warehouse is based to generally use historical trends in data.
This has a been a guide to the top difference between Data Warehouse vs Database. Here we also discuss the Data Warehouse vs Database key differences with infographics, and comparison table. You may also have a look at the following articles to learn more