Both data warehouse and OLTP are relational databases.
Data Warehouse:
Designed for business measures analysis, by creation of attributes and categories
Does not cater to real time operational requirements of an enterprise.
Store house of current and historical data along with data extracted from external resources.
Bulk loads, unpredictable queries can access many rows for each table.
Data warehouse is loaded with valid, consistent data and real time validation is not needed.
Data warehouse is capable of supporting few concurrent users.
OLTP:
Designed for performing transaction of real time business records.
Caters to real time operational requirements of an enterprise.
Optimized for a set of transactions, which are like adding and retrieving single row at a time for each table.
OLAP is optimized for validating incoming data at the time of transactions. It uses validation data tables.
OLAP is capable of supporting thousands of concurrent users.
Data Warehouse:
Designed for business measures analysis, by creation of attributes and categories
Does not cater to real time operational requirements of an enterprise.
Store house of current and historical data along with data extracted from external resources.
Bulk loads, unpredictable queries can access many rows for each table.
Data warehouse is loaded with valid, consistent data and real time validation is not needed.
Data warehouse is capable of supporting few concurrent users.
OLTP:
Designed for performing transaction of real time business records.
Caters to real time operational requirements of an enterprise.
Optimized for a set of transactions, which are like adding and retrieving single row at a time for each table.
OLAP is optimized for validating incoming data at the time of transactions. It uses validation data tables.
OLAP is capable of supporting thousands of concurrent users.
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