by Database System
Database System is used in traditional way of storing and retrieving data. The major task of database system is to perform query processing. These systems are generally referred as online transaction processing system. These systems are used day to day operations of an organization.
Characteristics of Database
- Offers security and removes redundancy
- Allow multiple views of the data
- Database system follows the ACID compliance (Atomicity, Consistency, Isolation, and Durability).
- Allows insulation between programs and data
- Sharing of data and multiuser transaction processing
- Relational Database support multi-user environment
Data Warehouse
Data Warehouse is the place where huge amount of data is stored. It is meant for users or knowledge workers in the role of data analysis and decision making. These systems are supposed to organize and present data in different format and different forms in order to serve the need of the specific user for specific purpose. These systems are referred as online analytical processing.
Characteristics of Data Warehouse
- A data warehouse is subject oriented as it offers information related to theme instead of companies’ ongoing operations.
- The data also needs to be stored in the Dataware house in common and unanimously acceptable manner.
- The time horizon for the data warehouse is relatively extensive compared with other operational systems.
- A data warehouse is non-volatile which means the previous data is not erased when new information is entered in it.
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Database |
Data Warehouse |
| Operational systems are designed to support high-volume transaction processing. | Data warehousing systems are typically designed to support high-volume analytical processing (i.e., OLAP). |
| Data within operational systems are mainly updated regularly according to need. | Non-volatile, new data may be added regularly. Once Added rarely changed. |
| Operational systems are usually concerned with current data. | Data warehousing systems are usually concerned with historical data. |
| It is designed for real-time business dealing and processes. | It is designed for analysis of business measures by subject area, categories, and attributes. |
| It is optimized for validation of incoming information during transactions, uses validation data tables. | Loaded with consistent, valid information, requires no real-time validation. |
| It is optimized for a simple set of transactions, generally adding or retrieving a single row at a time per table. | It is optimized for extent loads and high, complex, unpredictable queries that access many rows per table. |
| It supports thousands of concurrent clients. | It supports a few concurrent clients relative to OLTP. |
| Operational systems are widely process-oriented. | Data warehousing systems are widely subject-oriented |
| Operational systems are usually optimized to perform fast inserts and updates of associatively small volumes of data. | Data warehousing systems are usually optimized to perform fast retrievals of relatively high volumes of data. |
| Less Number of data accessed. | Large Number of data accessed. |
| Relational databases are created for on-line transactional Processing (OLTP) | Data Warehouse designed for on-line Analytical Processing (OLAP) |
| Data In | Data Out |
