Contrasting OLTP and Data Warehousing Environments

Contrasting OLTP and Data Warehousing Environments:

One Major difference between the types of system is that data warehouses are not usually in third normal form (3NF), Which is commonly used in OLTP environments.

Data warehouses and OLTP systems have very different requirements. Here are some examples of differences between typical data warehouse and OLTP systems:

(i)                   Work Load:

Data warehouses are designed to accommodate ad hoc queries. You might not know the workload of your data warehouse in advance, so a data warehouse should be optimized to perform well for a wide variety of possible query operations.

OLTP systems support only predefined operations. Your applications might be specially tuned or designed to support only these operations.

(ii)                 Data Modifications:

A data warehouse is updated on a regular basis by ETL process (run nightly or weekly) using bulk data modifications techniques. The end users of a data warehouse don't directly update the data warehouse.

In OLTP systems, end users routinely issue individual data modifications statements to the database. The OLTP database is always up to date, and reflects the current state of each business transaction.

(iii)                Schema Design:

Data warehouses often use demoralized or partially demoralized schemas (such as star schema) to optimize query performance.

OLTP systems often use fully normalized schemas to optimize update/ insert/ delete performance, and to guarantee data consistency.

(iv)               Typical Operations:

A typical data warehouse query scans thousands or millions of rows. For example, "Find the total sales for all customers last month ".

A typical data warehouse operation accesses only a handful of records. For example, "Retrieve the current order for this customer ".

(v)                 Historical Data:

Data warehouses usually store many months or years of data. This is to support historical analysis.

OLTP systems usually store data from only a few weeks or months. The OLTP system stores only historical data as needed to successfully meet the requirements of the current transaction.