Skip to main content


Enterprise Systems and IT Application can be categories in two types OLTP and OLAP. In General Terms OLTP is day to day Record Keeping of any organization and OLAP is the Historical Data of Warehouse..  

OLTP (On-line Transaction Processing) is characterized by a large number of transactions (INSERT, UPDATE, DELETE). 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. In OLTP database there is detailed and current data, and schema used to store transactional databases is the entity model (usually 3NF)

OLAP (On-line Analytical Processing) is characterized by relatively low volume of transactions. Queries are often very complex and involve aggregations(DISTINCT,GROUP BY,SUM,COUNT ..). For OLAP systems a response time is an effectiveness measure. OLAP applications are widely used by Data Mining techniques. In OLAP database there is aggregated, historical data, stored in multi-dimensional schemas (usually star schema).

Major differences between OLTP and OLAP system is below :-

(Operational System)
(Data Warehouse)
Time Scale
This stores current data
This stores History data for analysis
Backup and Recovery
Backup religiously; operational data is critical to run the business, data loss is likely to entail significant monetary loss and legal liability
Instead of regular backups, some environments may consider simply reloading the OLTP data as a recovery method
Examples for OLTP Queries:
What is the Salary of Mr.John?
How is the profit changing over the years across different regions ?
Examples for OLTP Queries:
What is the address and email id of the person who is the head of maths department?
Is it financially viable continue the production unit at location X?
Scattered among different databases or DBMS and using different value coding schemes
Centralized in data warehouse. Or in a collection of subject oriented data marts
Optimizes update performance by minimizing the number of indexes
Optimizes adhoc queries by including lots of indexes
Inserts and Updates
Short and fast inserts and updates initiated by end users
Periodic long-running batch jobs refresh the data
This is fully normalized
Possibly partially denormalized for performance reasons. As this is used for reporting
Data stored revolves around business functions
Data stored revolves around information topics
Processing Speed
Typically very fast
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
Purpose of data
To control and run fundamental business tasks
To help with planning, problem solving, and decision support
Relatively standardized and simple queries Returning relatively few records
Often complex queries involving aggregations
Source of data
Operational data; OLTPs are the original source of the data.
Consolidation data; OLAP data comes from the various OLTP Databases
Space Requirements
Can be relatively small if historical data is archived
Larger due to the existence of aggregation structures and history data; requires more indexes than OLTP
Stored Values
Stores typically coded data
Stores descriptive data
What the data
Reveals a snapshot of ongoing business processes
Multi-dimensional views of various kinds of business activities

Reference :- Wikipedia, MSDN.

Thanks for reading.....


Popular posts from this blog

mongoDB error : aborting after fassert() failure

What to do when facing errors on mongoDB “aborting after fassert() failure”

I like errors, in mongoDB this is the first error I faced and luckily many times. This error i faced during restoring name-space on local and restarting db system. I am still searching the exact root cause of this issue but i am able to resolve the current problem through below steps.

Remove all relevant namespace files from data-file route path..Now repair mongo instance using mongod process.mongod --repair ////////// execute command from bin folder path Then start server using mongd process, if started server successfully then ..mongod  ////////// execute command from bin folder path Restore last backups as normal process.Now check database by connecting mongo shell. Thanks for reading, 
Please comment your experience if you faced and also share knowledge if you have better steps to resolve...

SQL71562: external references are not supported when creating a package from this platform

Last week I got this error from one of developer who was trying to deploy his project from Testing server to SQL Azure QA server. He was using “Deploy Database to SQL Azure” option from SSMS Tool-Task option.

After connecting to SQL Azure portal when operation started to deployment below errors occurs.

Validation of the schema model for data package failed. Error SQL71562: Error validating element has an unresolved refrence to object xx.dbo.xxxx external refrences are not supported when creating a package from this platform.

Reason: The reason of the this error was; some functions of project was dependent on master database and only single database was being deploy to SQL Azure. DACFx must block Export when object definitions (views, procedures, etc.) contain external references, as Azure SQL Database does not allow cross-database external references So, this error was coming.

Solution : I suggested him to create those function to locally on local database what…

How to add an article in Transactional Replication

If we have a set-up of Transactional Replication for Data Distribution running and wanting to add new object to replication on other server we can follow below process.
To add an article In Transaction replication with PUSH Subscription