Cloud database, definition
Cloud databases are databases built, deployed, and accessed in cloud environments such as private, public, or hybrid clouds.
There are two main cloud database deployment models, as follows:
traditional cloud database
Much like the database managed internally on site, except for the infrastructure configuration. In this case, an organization purchases virtual machine space from a cloud service provider and deploys the database to the cloud. The organization's developers use a DevOps model or traditional IT staff to control the database. This organization is responsible for oversight and database management.
Database as a Service (DBaaS)
In which the organization contracts with the cloud service provider through a fee-based subscription service. Service providers provide various real-time operations, maintenance, administration, and database administration tasks to end users. The database runs on the service provider's infrastructure. This usage model typically includes automation in the areas of configuration, backup, scaling, high availability, security, patching, and health monitoring. The DBaaS model provides the greatest value to organizations by enabling them to use outsourced database administration optimized through software automation, rather than hiring and managing in-house database experts.
Benefits of cloud databases
Cloud databases offer many of the same benefits as other cloud services, including:
Increase agility and innovation. Cloud databases can be set up and decommissioned very quickly, making it easy and fast to test, validate and implement new business ideas. If an organization decides not to implement a project, it can simply abandon the project (and its database) and move on to the next innovation.
Faster time to market. With cloud databases, there is no need to order hardware or spend time waiting for shipping, installation, and network setup while new products are in the development queue. Database access can be completed within minutes.
reduce risk. Cloud databases present numerous opportunities to reduce risk across the enterprise, especially for DBaaS models. Cloud service providers can use automation to enforce security best practices and capabilities and reduce the likelihood of human error (a leading cause of software downtime). Automated high availability features and service level agreements (SLAs) can reduce or eliminate lost revenue due to downtime. Capacity forecasting is no longer a critical issue when implementing projects, as the cloud can be an infinite pool of instant infrastructure and services.
cut costs. A pay-as-you-go subscription model and dynamic scaling allow end users to provision at a steady state, then scale up during busy periods based on peak demand, and then scale back when demand returns to steady state. This is much less expensive than maintaining these functions in-house, where organizations must purchase physical servers that can handle peak demand, even though they may only need the peak function for a few days per quarter. Businesses can save money by turning off services when they are not needed. They can also reduce costs by executing global initiatives with marginal infrastructure investments. In many cases, cloud software automation replaces high-cost database administrators (DBAs), reducing operational expenses by eliminating the need for expensive in-house resources.
Cloud databases can also combine transaction processing, real-time analytics across data warehouses and data lakes, and machine learning in one database service without the complexity, latency, cost, and risk of extract, transform, and load (ETL) duplication .
