Featured Database Articles
The term UPSERT has been coined to refer to an operation that inserts rows into a table if they don’t exist, otherwise they are updated. To perform the UPSERT operation Microsoft introduced the MERGE statement. Not only does the MERGE statement support the UPSERT concept, but it also supports deleting records. Greg Larsen discusses how to use the MERGE statement to UPDATE, INSERT and DELETE records from a target table.
One of the primary advantages of Platform-as-a-Service (PaaS) solutions offered by Microsoft Azure is the ease with which scaling can be implemented. While SQL Database facilitates both vertical and horizontal scaling approaches, scaling it out is considerably more challenging. In this article, we will provide a high-level overview of both vertical and horizontal scaling methods available with Azure SQL Database.
Arshad Ali discusses how to use CTE and the ranking function to access or query data from previous or subsequent rows. He also shows you how to leverage the LEAD and LAG analytics functions to achieve the same result without writing a self-join query using CTE and ranking function.
Performance is the watchword with a database and indexes can be a major part of that performance equation. Oracle provides the optimizer_index_cost_adj parameter but do you REALLY need to set it differently than the default? Read on to see what may happen when you do.
For business executives looking to save on information technology costs, it may seem like a win-win scenario in Oracle database environments to transition from Oracle Enterprise to Standard Edition. However, executives making this decision may not always be aware of or truly understand how transitioning from Enterprise to Standard Edition will affect the delivery of critical IT services, ultimately creating the potential to impact end user efficiency and revenue.
Adaptive cursor sharing is a great feature that can tailor execution plans to bind variable values. Read on to see how it behaves when query order is reversed and if it chooses 'bad' execution plans.
Your big data repository won't simply add another twelve months of data over the next year. More data is coming, more categories of data will be created, and your analytical environment must expand to fit future needs. But size alone won't be your only problem. In the rush to accumulate a sufficient amount of valuable data and implement a business analytics environment that can produce usable results, several items may have been ignored, postponed, or simply forgotten. These missing details can make or break your company in the future.
Big data software, hardware, application suites, business analytics solutions ... suddenly, it seems, IT enterprises are deluged with vendor offerings that solve problems it didn't know it had. As you dive into what will most likely be your largest IT project of the year, ensure that you have planned and budgeted for the following items that are unique to big data implementations.
It’s difficult to simply 'drop' big data applications into an existing IT infrastructure and expect to run smoothly. In addition to energy and cooling requirements for new hardware to support the new big data application, other IT areas need to prepare. The major factors that determine whether enhancements will be needed to existing applications include large data storage needs, larger data transmission capacity, and the demands these will place on existing hardware and software.