Leave the most complex parts of managing relational databases to us and easily scale up as demand increases
Administering and managing databases with multiple tables can get complicated quickly—to say nothing of actually querying those databases. A managed relational database offers all the convenience of a neatly organized collection of data across tables and none of the managerial complexities of putting that data to use.
A relational database stores its data in one or more tables consisting of rows and columns, where each row represents a thing and each column represents something about that thing. Attributes label each column and row so users can relatively easily compare data point to data point.
In the simple example database above, there are four rows and five columns. Each column contains information about an attribute of the student and a relational key from each row. A user can query this database to answer a question about how tall Jess is, or how much they weigh. The ID column assigns a unique key to each row to make querying the database faster.
Typical databases contain many more values and variables than this one does—in fact, it’s not unusual for databases to contain millions of records—which is one of the reasons why managing a database can become a complex task.
Relational databases are also commonly called SQL databases because they’re all written in SQL (Structured Query Language), a coding language used to execute queries, edit data, and fetch data from the database.
A relational database management system (RDBMS), meanwhile, is merely the interface or software a person might use to manage, query, or otherwise interact with their relational databases.
A managed relational database is a cloud computing service in which a user pays a cloud service provider to create and manage a database. Unlike an on-premises database, users don’t have to set up or maintain a database on their own and instead outsource the responsibility to oversee the database’s infrastructure to the database provider.
Typically, maintaining a database takes time and expertise that most developers don’t have. Databases need to be provisioned, configured, and continually maintained so relations aren’t broken as more data is added.
There are a host of benefits to using a managed relational database:
Secure, reliable data storage is more important than ever for companies of every size. At DigitalOcean, we offer secure managed relational database services—supporting MySQL and PostgreSQL database engines, among others—that are also flexible enough to meet the needs of growing businesses.
Launch in just a few clicks, access it via our simple UI or an API—and never worry about maintenance operations or updates again.
Scale-up at any time to support your business as it grows; easily spin up more nodes to scale read operations.
Your data is backed up automatically every day so you can restore it to any point within the previous seven days.
Databases run in your account’s private network, only whitelisted public internet requests will reach your database, and all data is encrypted in transit and at rest.
In the event of a failure, a standby node with a copy of your data automatically replaces the problem node to minimize downtime.
Databases run on enterprise-class hardware giving you lightning-fast performance, whether virtual machines run on shared or dedicated CPUs.
Spin up PostgreSQL and MySQL databases on DigitalOcean.
SQL is a coding language designed specifically for managing data in relational databases. Fun fact: The International Organization for Standardization made SQL the standard database language in 1987.
ACID is a set of database transaction properties that ensure data validity in operations, like transferring money between two bank accounts, despite errors, accidents, and mishaps. All databases need to demonstrate the four ACID properties to be considered ACID-compliant:
There are several key differences between relational databases and object-oriented databases:
You can scale a relational database both vertically and horizontally. To scale vertically you would add more capacity to a server such as more CPU and disk power to enhance your storage process. Scaling vertically could also involve mormalisation by splitting data within columns into separate tables.
Another alternative is to scale horizontally by adding more machines. Scaling horizontally can also involve sharding or splitting a row into separate tables
It depends entirely on your use case, typically you would consider relational databases when you have simple, predictable, and structured data like financial information. It’s not uncommon to use both relational and object-oriented databases together for the same use case to take advantage of the best of both worlds.
If your data is structured as a hierarchy or a network it may not be the right fit for relational databases, because it can be a challenge to go through several tables using keys to chase what you are looking for. Apps that are read-mostly do not benefit from relational databases as there is a lot of overhead for simple read access. Finally, if you have no expectation of unexpected queries a relational database isn’t needed.