Featured Database Articles
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.
Marcin Policht presents different methods that allow you to monitor the performance and characteristics of your PaaS databases, ensuring that they behave in a manner that matches your expectations.
Greg Larsen explores how to remove rows from a SQL Server table using the DELETE statement.
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.
Oracle offers Deferred Segment Creation for tables and indexes, which allows users with no access to a tablespace to create tables and indexes successfully. Read on to see why this is a problem.
Bloom filters can improve performance in recent Oracle releases, but Oracle 18.104.22.168 provides the In-Memory Database option and using that configuration can improve performance even further. Read on to see how the in-memory option is configured and the performance it provides.
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.
Big Data implementations are more than just lots of data. Of equal importance is the analytics software used to query the data. Analyzing business data using advanced analytics is common, especially in companies that already have an enterprise data warehouse. It is therefore only natural that your big data application must be integrated with the existing warehouse.