Transactional DatabaseAnalytical Database
Operational SystemsData Warehousing
Original source of dataData comes from varies sources
Large number of transactions.Low number of transaction.
Very fast query processing Queries are often very complex and involve aggregations
Detailed and current data, and schema is the entity model (usually 3NF) Aggregated, historical data, stored in multi-dimensional schemas (usually star schema)
OLTP System 
Online Transaction Processing 
(Operational System)
OLAP System 
Online Analytical Processing 
(Data Warehouse)
Source of dataOperational data; OLTPs are the original source of the data.Consolidation data; OLAP data comes from the various OLTP Databases
Purpose of dataTo control and run fundamental business tasksTo help with planning, problem solving, and decision support
What the dataReveals a snapshot of ongoing business processesMulti-dimensional views of various kinds of business activities
Inserts and UpdatesShort and fast inserts and updates initiated by end usersPeriodic long-running batch jobs refresh the data
QueriesRelatively standardized and simple queries Returning relatively few recordsOften complex queries involving aggregations
Processing SpeedTypically very fastDepends on the amount of data involved; batch data refreshes and complex queries may take many hours; query speed can be improved by creating indexes
Space RequirementsCan be relatively small if historical data is archivedLarger due to the existence of aggregation structures and history data; requires more indexes than OLTP
Database DesignHighly normalized with many tablesTypically de-normalized with fewer tables; use of star and/or snowflake schemas
Backup and RecoveryBackup religiously; operational data is critical to run the business, data loss is likely to entail significant monetary loss and legal liabilityInstead of regular backups, some environments may consider simply reloading the OLTP data as a recovery method


Last modified: March 22, 2019



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