There's been a lot of discussion recently about autonomous databases, which offer the promise of keeping database systems stable and performant while alleviating much of the tuning and configuration drudgery that DBAs must typically slog through. It is important to note that an autonomous database needs to strike a balance between giving administrators too much and too little control. Too much control takes the form of endless configuration and tuning parameters that place the burden of performance and stability on the operator. Too little control takes the form of automated behaviors that reduce the predictability of the system to an unacceptable level.
Read More
One of the most important shifts in data warehousing in recent times has been the emergence of the cloud data warehouse. Previously, setting up a data warehouse required a huge investment in IT resources to build and manage a specially designed on-premise data center. Now, several cloud computing vendors offer data warehousing functions as a service (DWaaS), accessible via an Internet connection. This model negates the costly capital expenditure and management required for an on-premise data warehouse.
Read More
As the industry embraces artificial intelligence and marches toward autonomous systems, some enterprises will still need to rely on traditional databases that must be managed, tuned, and secured to ensure the best performance. And while not all organizations will be able to make the autonomous transition quickly due to internal processes, there are a few tricks to optimize your old database with terabytes of data at speeds needed for everything from e-commerce to IoT and music streaming services on a global scale.
Read More
Today, data management environments are highly complex and often span multiple vendors with deployments across on-premise data centers, clouds, and hybrid installations. In addition to the heterogeneity of systems, the processes surrounding database development and management have also changed. DevOps, a methodology for data scientists, developers, database administrators (DBAs) and others to participate in an Agile workflow, puts a premium on speed and also means that DBAs do not wield the firm control they did in the past.
Read More