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In an increasingly cloud-centric business environment, it only makes sense that enterprises are looking to the cloud as a venue for database management. But that doesn't mean you should implement one at breakneck speed without conducting due diligence. While cloud databases are the future of enterprise analytics, you'll need the right database management system (DBMS) and cloud architecture to deliver the most value from them.
What is a cloud database?
A cloud database is as its name suggests: a database deployed on a cloud platform. It can be either cloud-native or have been migrated from on-premises infrastructure. Every essential function you'd expect from a database is available in this context.
Enterprises can create a cloud database platform on their own by using space purchased from their public cloud provider. IT staff can oversee it as they would a traditional database, or developers can create a DevOps model for this purpose. Alternatively, they can have their cloud provider handle oversight and maintenance by opting for the database as a service (DBaaS) model, also known as a managed database. The latter involves an additional fee, but it may not necessarily be greater than the costs of running the database yourself—the question, then, becomes one of benefit-to-cost analysis.
Every major cloud vendor, such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud, offers a managed database service: RedShift or DynamoDB, Azure SQL Database or CosmosDB, and Google BigQuery, respectively. You can also choose a cloud database service from a provider specifically focused on the DBaaS vertical, or opt for the open-source relational database systems from MySQL and PostgreSQL.
Experts seem quite convinced that cloud databases are the way of the future: Gartner, for example, has projected that by 2022, about 75% of all databases will have migrated or been directly deployed to a cloud platform. Also, cloud DBMS solutions are expected to comprise 50% of the overall DBMS market by the following year.
The pros and cons of using cloud databases
By aligning your enterprise's database with the flexibility and scalability that the cloud offers, you can afford yourself the opportunity to realize some significant benefits.
Perhaps most notable of all these potential benefits is the ability to create an always-on database that is accessible anytime and anywhere—even via mobile. Multinational organizations with locations across multiple time zones, as well as a large number of employees working from home in disparate locations, will find this particularly advantageous. Cloud-based database and analytics operations allow your enterprise to adapt to changing dynamics, as seen with businesses' post-pandemic operational shifts.
Additionally, a cloud database solution can provide effective support of applications that rely on large data sets for efficient operation. It will allow your organization's developers to work on expanding app capabilities and take advantage of the most exciting cloud computing trends, without worrying about not having the necessary scale to do so.
Last but not least, the cloud makes it easy to run comprehensive data analytics operations that provide wide-ranging insights into your operations. Cloud databases also allow you to address various practical concerns: Costs will be notably lower than what you'd deal with if you wanted to expand your on-premises database system, and your administrators won't need to spend as much time managing the cloud database on a day-to-day basis.
All that said, a cloud database can pose some noteworthy challenges. Creating an in-house database within the cloud requires considerable time and resources. Opting for a DBaaS eliminates that difficulty, and is, generally speaking, the more common choice. But a managed cloud database may create its own problem in the form of vendor lock-in, especially if you only work with one cloud service provider. Additionally, despite the presence of disaster recovery and security features, you will likely still need to back up and protect the data you've stored in the cloud using other tools. There are practical ways to overcome these challenges, but you must always be prepared for them.
Considerations for selecting a cloud database
When looking for the ideal cloud-based database solution for your enterprise, several key factors should stay top of mind:
Database technology
Much in the same way data itself is broadly divided into two primary categories—structured and unstructured, albeit with countless variations between those poles—databases, cloud or otherwise, are either SQL or NoSQL. The fundamental difference is in the use of structured query language: SQL uses the language for which it's named, while NoSQL doesn't. Instead, NoSQL databases typically use procedural languages such as JavaScript, Python, and R alongside data frames to transform data into tabular formats for data science tools to consume.
Both SQL and NoSQL databases can handle structured or unstructured data, but SQL, by its relational nature, is better suited to structured data sets. The architecture of a NoSQL database is semi-structured, as Towards Data Science noted, so it works for either data type. Schemas can be set up in a number of ways to accommodate many types of unstructured data. NoSQL is arguably more popular due to its flexibility, but SQL can be ideal for handling multi-row transactions in accounting and finance applications.
Security
Cybersecurity is important for every enterprise, though the demands are greater on some than others. Key features to look for in a cloud database include:
- Always-on encryption, whether cloud data is at rest or in transit
- Role-based access control — each user can access exactly what data they need and no more
- Unified security policy management — especially important for transferring policies regarding on-premises data to the cloud
- Automated backups and patching
Cloud deployment
You may well be content with your current cloud service provider and its public cloud solution, and if so, using a single cloud for your database may work just fine. But even without the concern of vendor lock-in, putting all eggs into a single-cloud basket may be unwise for various reasons, including security and compliance.
A hybrid cloud architecture, which splits your resources between one or more clouds and your on-premises infrastructure, might be a better option. Choosing a multi-cloud deployment split across two or more public clouds from different vendors is another viable route.
Cloud database management with a versatile DBMS
Using a versatile cloud-ready DBMS will be integral to realizing the advantages of a cloud database. Such a tool is essential to overseeing access, movement, and optimal use of data, as well as reporting on key performance indicators (KPIs) across all areas of the enterprise to better shape organizational strategy.
Teradata Vantage can serve as your cloud database, and also runs on-premises. Simply put, you never lose sight of data no matter what path it travels, or whatever your intended use case may be: traditional or logical data warehouse needs, data science, deep learning, or operational intelligence. It offers support for streaming data pipelines, integration of all data types regardless of source of structure, machine learning and statistical functions to support the end-to-end data science experience, and many other features. To learn more about how Teradata customers have transformed their analytics operations with Vantage, take a look at our latest testimonials.
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