Featured Database Articles
Azure SQL Database offers several benefits, built into the underlying cloud infrastructure, that leverage resiliency and redundancy. You can take advantage of this functionality to facilitate failover and failback in response to events that affect availability of an Azure region. Read on to learn more.
Have you ever wondered how to find the worst performing TSQL queries on your instance? If you have, you are not alone.
Greg Larsen shows you how to determine if you are running the standard, enterprise, or developer edition of SQL Server.
Index-organized tables can provide great benefits if used properly. Read on to see how to use them and what you might run into if conditions aren't ideal.
An AWR report isn't the only source for total elapsed time for a query. Read on to see how to use the AWR data to compute these times on demand.
Oracle has two PGA size parameters that look the same but aren't. Read on to see what areas each covers and why you can't get them confused.
Big data applications were once limited to hybrid hardware/software platforms. Now, recent advances are allowing applications like these to be integrated with and federated into operational systems. In particular, IBM's DB2 for z/OS Version 12 delivers new features and functions that allow the DBAs to design, define and implement very large databases and business intelligence query platforms that fulfill some big data expectations.
Your big data application needs regular extracts from your production systems. While many best practices exist for big data extract, transform and load (ETL) processes, we sometimes forget that these data-intensive procedures can affect the operational environment’s performance. Here are some suggestions to mitigate such performance risks.
Big data applications start big and keep growing. As the masses of big data being analyzed grow both in size and complexity, the hardware and software communities have responded with huge storage offerings and massively parallel storage and retrieval mechanisms. The logical next step is for the IT enterprise to take advantage of these technological innovations for things other than classical big data processing.