We can divide IT systems into transactional (OLTP) and analytical (OLAP). In general we can assume that OLTP systems provide source data to data warehouses, whereas OLAP systems help to analyze it.
OLTP (On-line Transaction Processing):
- This system is characterized by a large number of short on-line transactions (INSERT, UPDATE, DELETE).
- OLTP System deals with operational data. Operational data are those data involved in the operation of a particular system.
- In an OLTP system data are frequently updated and queried. So quick response to a request is highly expected. Since the OLTP systems involve large number of update queries, the database tables are optimized for write operations.
- The main emphasis for OLTP systems is put on very fast query processing, maintaining data integrity in multi-access environments and an effectiveness measured by number of transactions per second.
- To prevent data redundancy and to prevent update anomalies the database tables are normalized (usually 3NF). Set of tables that are normalized and fragmented. Normalization makes the write operation in the database tables more efficient.
Example: In a banking System, you withdraw amount from your account. Then Account Number, Withdrawal amount, Available Amount, Balance Amount, Transaction Number etc are operational data elements.
OLAP (On-line Analytical Processing):
- This system is characterized by relatively low volume of transactions.
- In OLAP database there is aggregated, historical data, stored in multi-dimensional schemas (usually star schema).
- Updates are very rare in a Data warehouse. OLAP quiries will give aggregated information about the things happend in the past over a period of time and this will help the management in strategic decision making. Hence OLAP Queries are of having significant importance in strategic decision making.
Example: If we collect last 10 years data about flight reservation, The data can give us many meaningful information such as the trends in reservation. This may give useful information like peak time of travel, what kinds of people are travelling in various classes (Economy/Business)etc.
The following table summarizes the major differences between OLTP and OLAP system design.
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Another table to understand the differences -
OLTP System
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OLAP System
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Source of data
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Operational data; OLTPs are the original source of the data.
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Consolidation data; OLAP data comes from the various OLTP Databases
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Purpose of data
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To control and run fundamental business tasks
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To help with planning, problem solving, and decision support
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What the data
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Reveals a snapshot of ongoing business processes
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Multi-dimensional views of various kinds of business activities
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Inserts and Updates
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Short and fast inserts and updates initiated by end users
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Periodic long-running batch jobs refresh the data
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Queries
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Relatively standardized and simple queries Returning relatively few records
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Often complex queries involving aggregations
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Processing Speed
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Typically very fast
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Depends on the amount of data involved; batch data refreshes and complex queries may take many hours;
query speed can be improved by creating indexes
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Space Requirements
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Can be relatively small if historical data is archived
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Larger due to the existence of aggregation structures and history data; requires more indexes than OLTP
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Database Design
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Highly normalized with many tables
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Typically de-normalized with fewer tables; use of star and/or snowflake schemas
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Backup and Recovery
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Backup religiously; operational data is
critical to run the business, data loss is likely to entail significant
monetary loss and legal liability
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Instead of regular backups, some environments may consider simply reloading the OLTP data as a recovery method
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