A cloud database is a database that is built, deployed, and accessed in a cloud environment, such as a private, public, or hybrid cloud.
There are two primary cloud database deployment models, reviewed below:
Cloud databases offer many of the same benefits as other cloud services, including:
A cloud database 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 risks of extract, transform, and load (ETL) duplication.
Enterprises have choices in how to manage their cloud databases. Database management styles can be generalized into the following four categories:
There are numerous types of cloud databases, all of which are intended to meet specific needs and handle specific types of workloads. For example, there are databases specially designed to manage transactions, others designed to run internet-scale applications, and others that serve as data warehouses or data marts for analytics.
OLTP workloads are supported by data models that differ from those used in OLAP workloads. Document and multimedia data relies on formats like XML and JavaScript Object Notation (JSON). Other types of databases include graph databases used for connectivity analysis, spatial databases for geographic analysis, and key-value stores for high-performance storage and lookup of simple data types.
As commercial, enterprise databases have developed over time, they’ve begun to encompass multiple data models and access methods within a single database management system. What’s emerging in the industry today is a move toward the multimodel database that allows an end user to work across different types of workloads from one underlying database.
This new capability allows many applications to use the same database management system while the enterprise continues to benefit from the unique data models necessary for a specific application. These new database architectures are allowing enterprises to significantly streamline the number of databases they use and prevent the creation of data silos that lock an organization’s most valuable asset (data) away from broader use by the company.
Most every industry, from financial services to healthcare, can benefit from using cloud database solutions. The choice is not whether or not to use a cloud database. The choice is which model and type will work best to meet an enterprise’s specific needs.
Many organizations choose to take a staged approach to cloud database utilization, blending traditional cloud database models with DBaaS models. For others, such as those in the financial services industry, keeping mission-critical applications in-house could remain a priority.
However, things are changing quickly. As DBaaS models become more robust and the move to autonomous cloud databases takes hold, it’s likely that enterprises will find greater opportunities, and greater benefits, in fully migrating their databases to the cloud.
The newest and most innovative type of cloud database is the self-driving cloud database (also known as the autonomous database, referenced earlier). This database type uses cloud technology and machine learning to automate database tuning, security, backups, updates, and other routine management tasks.
Self-driving databases are designed to automatically withstand hardware failures, including those at cloud platform sites, and offer online full-stack patching of software, firmware, virtualization, and clustering. They easily scale performance and capacity as needed. Additionally, they protect data from both external attacks and malicious internal users, and they avoid many of the downtime-related issues of the other models—including planned maintenance.
IDC research indicates (PDF) that as much as 75% of an enterprise’s total data management costs can be in labor alone. A self-driving database could potentially save the average enterprise hundreds, or perhaps thousands, of full-time employee hours annually for every one of its major enterprise databases. In addition, it’s been estimated (PDF) that 72% of enterprise IT budgets goes to maintaining existing systems, leaving a mere 25% for innovation.
Self-driving databases could go a long way toward eliminating these high costs and allowing enterprises to utilize their DBAs on higher value work—such as data modeling, assisting programmers with data architecture, and planning for future capacity.
Gartner has touted cloud databases as one of the fastest-growing segments of the public cloud services market and expects database-platform-as-a-service (dbPaaS) revenue to reach almost $10 billion by 2021.
There are many vendors and options available to organizations looking for a cloud database solution for their enterprise. You’ll want to select a model that works best for your specific business needs. The following are some key features to look for from any cloud database:
Migrating a database to the cloud might sound like a daunting task, but it doesn’t have to be. Advance planning is the key. It’s also important to remember that not all migration methods apply to every scenario.
There are several factors to consider when choosing a migration method—including data types, host operating systems, and database versioning. Here are a few things to think about and prepare for as you approach the migration of your databases to the cloud.
Oracle’s automated tools allow you to seamlessly move your on-premises database to Oracle Cloud with virtually no downtime at all, because Oracle Cloud uses the same standards, products, and skills you currently use on-premises.