Tag Archives: database partitioning
Data warehouses tend to grow very quickly because they integrate data from multiple sources and maintain years of historical data for analytics. A number of our customers have data warehouses in the hundreds of terabytes to petabytes range. Managing such a large amount of data becomes a challenge. How do you curb runaway costs in such an environment? Completing maintenance tasks within the prescribed window and ensuring acceptable performance are also big challenges.
We have provided best practices to archive aged data from data warehouses. Archiving data will keep the production data size at almost a constant level, reducing infrastructure and maintenance costs, while keeping performance up. At the same time, you can still access the archived data directly if you really need to from any reporting tool. Yet many are loath to move data out of their production system. This year, at Informatica World, we’re going to discuss another method of managing data growth without moving data out of the production data warehouse. I’m not going to tell you what this new method is, yet. You’ll have to come and learn more about it at my breakout session at Informatica World: What’s New from Informatica to Improve Data Warehouse Performance and Lower Costs.
I look forward to seeing all of you at Aria, Las Vegas next month. Also, I am especially excited to see our ILM customers at our second Product Advisory Council again this year.
As one of the founders of Informatica’s Smart Partitioning capability, I am constantly asked, “Why can’t we just use (insert DB vendor here) tools to accomplish the same thing?” What a great, simple, straightforward question…and what a nuanced answer! Instead of talking about how great our technology is or walk through all the features and functionality, I thought it would be best to answer the actual question, “Why can’t we do this on our own?” In this two part series, we will explore the manual process of implementing Oracle database partitioning and compression in complex OLTP applications. (more…)
Alternative Methods of Managing Data Growth and Best Practices for Using Them as Part of an Enterprise Information Lifecycle Management Strategy
Data, either manually created, or machine generated, tend to live on forever, because people hold on to it for fear that they might lose information by destroying data.
There is a saying in Bhagavad Gita:
jaathasya hi dhruvo mr.thyur dhr.uvam janma mr.thasya cha |
thasmaad aparihaarye’rthe’ na thvam sochithum-arhasi ||
“For death is certain to one who is born; to one who is dead, birth is certain; therefore, thou shalt not grieve for what is unavoidable.” (more…)
Both partitioning and archiving are alternative methods of improving database and application performance. Depending on a database administrator’s comfort level for one technology or method over another, either partitioning or archiving could be implemented to address performance issues due to data growth in production applications. But what are the best practices for utilizing one or the other method and how can they be used better together?