Reduce the cost of compliance: database archiving and Information Lifecycle Management - Storage Management

Computer Technology Review, Dec, 2003 by Jim Lee

Database growth and storage issues are a top priority for large and small enterprises worldwide. Companies across industries rely on large, complex relational databases to support mission-critical applications. According to META Group, relational databases are growing at a rate of 125% annually. Compounding these challenges, data is stored across a variety of different database management systems, operating systems, hardware platforms and storage systems. These heterogeneous environments provide open, selective or restrictive access to application data for hundreds or thousands of users.

Experience shows that larger databases negatively impact application performance and take longer to load, unload, search, reorganize and recover. Response time can slow to the point where maintaining service levels can become nearly impossible. Batch processing windows expand, processing times overlap, and the start of routine operations is often delayed.

So, what are the alternatives? Database tuning? Expensive capacity upgrades? More storage? These options may abate the problems in the short term, but only offer diminishing returns because they only address the symptoms, while databases continue to grow. Data retention requirements and the need to manage and store information for longer periods are resulting in increased operational costs. Companies want to reduce IT costs and gain a greater return on their data management and storage investment. That is why Information Lifecycle Management (ILM) is considered an overall "best practice" approach, and database archiving is an essential component of ILM for managing database growth over the long term.

What is Active Archiving?

Unique to database archiving, active archiving is a proven strategy that allows organizations to archive rarely accessed data from application databases and manage the data efficiently, while providing easy access to data on demand. Archived data, business context data and metadata are saved to an Archive File (referentially intact and complete) and these files can be easily stored on the most convenient and cost-effective storage medium. Once archived, the data can be safely removed from application databases, improving the performance and availability of critical systems immediately. However, when needed, the archived data can be easily accessed, researched and selectively restored.

By separating essential data from nonessential data, many organizations can safely reduce the size of overloaded databases by up to 50% or more during the initial archive. Ongoing active archiving (daily, weekly or monthly) enables organizations to maintain mission-critical databases at a size that fits comfortably within the desired processing and disaster recovery windows. Routine backup and database maintenance processes take much less time. Mission-critical data is available at peak performance.

Most importantly, active archiving ensures data quality and referential integrity. Active archiving understands and remembers data relationships with 100% accuracy and saves not only the data, but also the metadata describing the tables, columns and relationships used to create the Archive File. Users continue to have real-time access to archived data using comprehensive search, browse and reporting capabilities without restoring a single row.

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With active archiving, users no longer need to restore all archived data for the sake of restoring a small subset of the data. Archived data can be restored selectively by specifying the criteria that identifies the data to be restored, even if it differs from the original criteria used to archive the data. Active archiving also ensures that data can be restored to a new or existing database, even if the data model has changed over time. So, how does active archiving complement ILM and reduce the cost of compliance?

Managing the Information Lifecycle

All information has a lifecycle, from acquisition through disposal (see Figure 1). During this period, the data access requirements range from heavily accessed to rarely accessed. At each stage in the lifecycle, the business value of the information, as well as the access rates and performance requirements will vary. In general, for any given type of information, you should be able to compare the business value against the cost to store and access it in a timely manner.

You can reduce the storage and operational costs associated with data retention, and reduce the cost of compliance, by matching the storage medium to the access and performance requirements corresponding to the business value of the data. In other words, to achieve an optimal return on investment, you should manage and store data in a way that matches its business value.

Basically, data is most valuable once it is created, or soon thereafter. As data ages, the relative value and the corresponding access rates decrease. There comes a point of diminishing returns where the cost to provide optimal production-level access and performance outweighs the actual business value derived from the data. At this point, it makes sense to move your data out of the high-cost, fast response system and into lower-cost, slower response systems to better match its business value. Although ILM is a simple concept, implementing ILM can be highly challenging, especially for managing complex relational data. Database archiving is the critical component within any ILM framework that enables companies to manage relational data according to its business value.