A cloud database is a database service built and accessed through a cloud platform. It serves many of the same functions as a traditional database with the added flexibility of cloud computing. Users install software on a cloud infrastructure to implement the database.
Users can access cloud databases from virtually anywhere, using a vendor’s API or web interface.
Cloud databases can expand their storage capacities on run-time to accommodate changing needs. Organizations only pay for what they use.
In the event of a natural disaster, equipment failure or power outage, data is kept secure through backups on remote servers.
Control options: Users can opt for a virtual machine image managed like a traditional database or a provider’s database as a service (DBaaS).
Database technology: SQL databases are difficult to scale but very common. NoSQL databases scale more easily but do not work with some applications.
Security: Most cloud database providers encrypt data and provide other security measures; organizations should research their options.
Maintenance: When using a virtual machine image, one should ensure that IT staffers can maintain the underlying infrastructure.
Managing engagement and application data for massive networks of mobile users or remote devices can be a scalability and availability nightmare.
The problem is that most databases require updates to occur in a central “master” database. This can result in performance bottlenecks and also prevent applications from running if the connection to the master database is unavailable.
A cloud database such as IBM Cloudant® enables you to push database access to the farthest edge of the network, such as mobile devices, remote facilities, sensors, and Internet-enabled goods, so you can scale bigger and enable applications to continue running while offline.
Hybrid databases create a distributed hybrid data cloud for increased performance, reach, uptime, mobility, and cost savings:
This is the path to hybrid cloud that accommodates growing data management needs, not infrastructure needs. Organizations can continuously optimize the data layer for cost, performance, security, and reach. They can break up their data, distribute it, and move it closer to their users.
For example, financial organizations are embracing the hybrid concept by using the database as a central repository for all their disparate data sources, and then delivering this financial data in JSON format. This data is then distributed to the database as a service and replicated to geographic regions across the world.
If a customer in Singapore has to wait more than four seconds for their mobile application data to be retrieved from a database in New Jersey, that customer is not likely to use that application again. Database-as-a-service can replicate and distribute immediately and offer near real-time access to data worldwide.
Cloud databases can collect, deliver, replicate, and push to the edge all your data using the new hybrid cloud concept. Users no longer have to deploy the dependent middleware to deliver database requests anywhere in the world. They can connect applications directly to their database.
The data layer for hyperscale, resilient, globally available applications, based on open source Apache CouchDB.
IBM Db2 is the cloud-native database built to power low latency transactions and real-time analytics at scale.
Predict outcomes faster using a platform built with data fabric architecture. Collect, organize and analyze data, no matter where it resides.
A relational database organizes data into linked, or related, tables. Analysts use structured query language (SQL) to explore, summarize and report on data in relational databases.
NoSQL is an approach to database design that enables the storage and querying of data outside the traditional structures found in relational databases.