What Is a Cloud Database?

A cloud database is a database built and deployed on cloud infrastructure. A database is an electronically stored, systematic collection of data. Traditionally, organizations had to set up and run database software on-premises. Today, organizations can access database technology as a cloud service over the Internet. Cloud databases have increased accessibility and scalability, allowing organizations to get more value from their data.

Cloud databases come with a range of features

Scalability

Cloud database solutions automatically scale I/O to match your application requirements. The size of your database volume automatically increases as your storage needs grow. You don't need to provision excess storage for your database to handle future growth. Businesses can manage growing data and fluctuating workloads without compromising performance.

High availability

Most cloud database solutions offer built-in high-availability features, such as automatic failover, replication, and multi-region support. They replicate data globally so you can bring data geographically closer to your end users. Your database remains accessible even during hardware failures or regional outages. You also get automated backups and disaster recovery options for uninterrupted operations.

Interoperability

Cloud databases integrate with other cloud services and third-party tools. They support many APIs, SDKs, and connectors, so you can integrate them with the data processing tools of choice. The interoperability enhances the database's utility in a broader tech ecosystem.

Generative AI integration

Some cloud database platforms allow generative artificial intelligence (AI) and machine learning (ML) and models to access data directly and run in the database. You can access vector database capabilities to store, search, index, and query ML embeddings representing the semantic meaning of content.

Monitoring

Cloud databases have integrated monitoring and alerting tools that provide real-time insights into database performance, resource usage, and potential issues. You also get versioning and auditing features to track data changes over time.

Cloud databases offer the flexibility and convenience of cloud computing.

Scale automatically

Cloud databases autoscale horizontally and distribute their workloads across multiple nodes. They can scale up or down automatically with changing workloads, so businesses can experiment with new projects without worrying about hitting resource limits.

Reduce costs

Traditional on-premise databases require substantial capital investment in hardware, software licenses, and ongoing maintenance. In contrast, cloud databases operate on a pay-as-you-go model. You only pay for the resources you consume, eliminating the need for over-provisioning. Additionally, you can leverage innovations like I/O optimization for additional price-performance benefits.

Increase performance

Cloud databases leverage the latest networking, storage, and processing technology to deliver exceptional performance. You can store data closer to end-users and reduce latency. Features like automated load balancing, caching, and database optimization support performance at scale.

Safeguard your data

Cloud databases support encryption at rest and in transit. Advanced authentication mechanisms, such as multi-factor authentication (MFA) and role-based access control (RBAC), prevent unauthorized access. You can choose network isolation and advanced auditing to help meet the strictest regulatory requirements.

Simplify operations

Cloud providers offer a range of automated tools for database provisioning, patching, backups, and scaling to save time and reduce the risk of human error. Cutting-edge technologies like zero-ETL enable near-real-time analytics and machine learning. Scale instantly with serverless with zero downtime. Organizations can focus on core activities over database management.

All major database technologies are supported in the cloud. You get various options to flexibly choose the best one for your application.

Relational databases

Relational cloud databases, or SQL databases, are structured around tables with rows and columns. Primary and foreign keys define relationships between data points. They are ideal for complex queries, transactions, and strong data consistency applications. Examples include cloud-based versions of traditional databases such as MySQL, PostgreSQL, and MariaDB.

Non-relational databases

Non-relational cloud databases offer flexibility in data storage and structure. They are designed to handle unstructured or semi-structured data and can accommodate a variety of data models.

In-memory databases

In-memory databases store data in main memory (RAM) during processing, allowing for extremely fast data retrieval and processing. They are often used for caching, session management, and real-time analytics.

Key-value databases

Key-value databases store data as a collection of key-value pairs. Each key is unique and maps to a string, number, complex object, or other data type. It is suitable for scenarios where quick lookups and flexible data storage are needed. Common use cases include user session management and caching.

Document databases

Document databases store data in document formats, like JSON or BSON. Each document is a self-contained data unit that can be nested and varied in structure. Document databases are commonly used in content management systems and e-commerce platforms.

Graph databases

Graph databases use graph structures with nodes, edges, and properties to represent and traverse relationships between data points. This model excels in scenarios where relationship queries are complex, and performance is critical.

Search databases

Search databases are optimized for indexing and querying large volumes of text data, allowing full-text search capabilities and fast information retrieval. These databases are often used in search engines or log analysis.

Time series databases

Time series cloud databases are optimized for storing and querying time-stamped data. Features like fast aggregation and trend analysis make them suitable for monitoring systems, financial trading, and IoT sensors.

There are three ways you can choose to run your cloud database.

Self-managed

In a self-managed cloud database, you migrate your existing on-prem database to the cloud. You set up and configure your cloud instances(servers), then move your database from on-prem to the cloud. You get flexibility and agility but retain database management responsibility. You still have to patch, update, scale, and otherwise maintain your database solution in the cloud.

Fully managed

You access your cloud database as a fully managed database service. The cloud provider takes responsibility for many tasks like provisioning, software patching, setup, configuration, and backups. Instances automatically increase storage size with zero downtime. You can choose from fully managed versions of your familiar database solution or move to specialized cloud database services for optimum performance.

Serverless

Serverless cloud database solutions take fully managed to the next level. You do not have to think about server environments at all. They automatically start and shut down to suit your requirements. An advanced serverless cloud database can scale instantly to hundreds of thousands of transactions in a fraction of a second. As it scales, it adjusts capacity in fine-grained increments to provide the right database resources your application needs. You pay only for the capacity your application consumes.

Database migration is the process of moving on-prem data to the cloud database. Some strategies to use include:

Lift and shift

You keep the data as is and transport it without any transformation. While effective, it may not help you capitalize on the full benefits of your cloud database.

Use preexisting tools

Database migration software tools make the entire process much simpler to manage. For example, AWS Database Migration Service helps move your database workloads to AWS with minimal downtime and zero data loss.

Enlist specialist help

For complex migrations, it can be wise to enlist the help of outside experts. In cloud database migration to AWS, you can choose to connect with one of our AWS Partners.

Databases on AWS provide purpose-built cloud databases for any enterprise. AWS cloud database solutions support all database management tasks. As your cloud service provider, AWS continuously monitors your databases and automates scaling. For example

• Amazon Relational Database Service (Amazon RDS) is a managed service that makes it easy to set up, operate, and scale a relational cloud database.
• Amazon Aurora is a fully managed relational cloud database service that automates time-consuming tasks such as provisioning, patching, backup, recovery, failure detection, and repair.
• Amazon Neptune is a graph-oriented cloud database that can execute more than 100,000 queries per second.
• Amazon ElastiCache is an in-memory NoSQL cloud database.

Read about how to choose a database, or get started by creating a free AWS account today.