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Smarter Archiving : Method for designing automatic archiving at design stage. Disclosure Number: IPCOM000240300D
Publication Date: 2015-Jan-21
Document File: 3 page(s) / 145K

Publishing Venue

The Prior Art Database


We are living in an era where digital data growth is quite exponential. So, every business/industry looking for innovative methods to proactively control this data growth otherwise it will start impacting their applications, storage and more importantly performance i.e. time to access data. At present, whatever archiving solutions available in market lies in reactive way to problem, i.e. when it starts effecting the business. Disclosed is a method in which archiving strategy is defined within the database product at the design stage of database structures. This will lead relational databases to keep track of their data growth from the early stages. In addition, it could avoid planning for separate archive solution.

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Smarter Archiving : Method for designing automatic archiving at design stage .


Almost all organizations depend on business- critical applications to meet the challenges of daily operations-from payroll processing and financial reporting to customer service and support. These applications manage essential information for transaction processing and helps in timely decision making. Every day piles of data get added to underlying databases of these applications. This uncontrolled data growth can impair- timely completion of critical business activities, getting access to required data within acceptable response limits and many other issues. All this impact organizations from meeting its service-level agreements (SLAs).

Once business start analyzing such problem which points to un-controlled data growth- generally policy decisions are made to look for appropriate archiving solution. Then set of business & technical people gets interlocked who start investigating database structures. These analysts examines business data contained in tables and come out with data analysis report and required archiving strategy- according to frequency, its necessity to business and various other factors.

There are various data archiving solutions available in market e.g. IBM's InfoSphere Optim data growth, Informatica , HP's Outerbay and Solix etc.

Archiving at design stage of database

This article identifies need for planning for data archiving at the database design stage. All steps and details in this paper not specific for any database product rather it describe methodology of designing data archiving at the data structure design.

As entity's properties, its attributes and domain values are well understood at design time, hence their useful to business and lifecycle associated in database can be designed better. Also, addressing such issues in the earlier phase shortens the time required to define policies around archiving data significantly in later stage. For systems running for a very long time using this method (designing Archiving at database design time) could help track its data growth more or less automatically.

Disclosed is a method in which data archive functionality gets implemented at database design stage (entity creation) in database product itself, so database volume going out of control in future can be avoided completely. This will identify rows as per the archive criteria defined and automatically move this out from database, using chosen data unload method of database product, and also marked the successful rows with archive identifier. Later optionally deletes the archived data from the system automatically.

This method helps in archiving data and moving this out of system with desired parameter without any special planning. e.g. business made a policy decision of keeping all data out of production databases if they are not accessed in last 2 years or any data older than 5 years. So method and process internal to data...