Featured Database Articles
Marcin Policht reviews security related challenges of Microsoft Azure Software as a Service-based SQL Database, focusing in particular on the SQL Server and database-level firewall access control functionality and methods that can be employed to implement it.
Greg Larsen provides a quick primer of the new Dynamic Management Views (DMVs) to help you better understand and manage your In-Memory OLTP tables and your Instances that support In-Memory OLTP tables.
PowerShell provides a command-line shell and scripting language (built in the .NET Framework) especially designed for administrative task automation and configuration management. Read on to learn how to manage Windows services related to SQL Server, either on a local machine or remote machine, using PowerShell cmdlets.
With a product as complex as Oracle some bugs are bound to be present. Some of these bugs are show-stoppers, and others aren't, but it does teach you to pay careful attention to the results a query delivers. Even though queries are syntactically and logically correct you can't be certain that Oracle won't do something 'behind the scenes' that can produce the wrong answer.
Do you really need an RMAN catalog to successfully recover your Oracle database? There are those that think so -- but they would be wrong. Read on to find out what you need to recover your database without a catalog.
In Release 11.2, Oracle has provided three improvements to earlier attempts at controlling parallel execution. These improvements make this feature more manageable, more scalable, and less likely to saturate server resources, such as memory and CPU, than earlier releases of the database. David Fitzjarrell discusses the first of those improvements, parallel statement queuing.
Big data applications and their associated proprietary, high-performance data stores arrived on the scene a few years ago. With promises of incredibly fast queries, many IT shops implemented one or more of these combination hardware and software suites. However, few IT enterprises have implemented metrics that clearly measure the benefits of these systems. The expected monetary gains from big data applications have not yet materialized for many companies, due to inflated expectations. The solution: Measure resource usage, and use these measurements to develop quality metrics.
Load tests give the database administrator (DBA) quite a lot of valuable information and may make the difference between poor and acceptable application performance. But what about a big data environment? Are there any gotchas or traps associated with big data?
With all of the news, articles, white papers and vendor products related to Big Data, it’s easy to forget the data that drives our companies, manages sales, interacts with customers, and supports our mission-critical systems--the "other" data ... the "little" data. If we want to incorporate big data into our enterprise the crucial step is integrating in with our existing data.