It’s no secret that we have more data today than we know what to do with. Modern technology has enabled us to gather, store, and analyze massive amounts of data to make informed business decisions — from how we design new applications to how we segment customers and everything in between.
However, many organizations struggle to take full advantage of their data. Commercial databases often don’t have the capabilities or capacity to handle the volume, velocity, or variety of modern data (the 3 V’s of big data).
As a result, enterprises are migrating away from inflexible commercial database vendors to agile cloud providers, like Amazon Web Services (AWS), which outperform legacy products on several fronts. AWS offers a wide selection of purpose-built databases that can scale to any size, support innovative applications, and enable any data model.
Here, we discuss four reasons why organizations with ambitious data goals should move their databases away from commercial providers to the cloud. We also share why it helps to have a cloud expert like ClearScale on your side when facing a large-scale database migration.
AWS Databases: Cost-effective Pricing
In many cases, commercial databases are more expensive than cloud-based databases because of their inflexible pricing. Commercial vendors typically charge annual fees for maintenance and lock access to certain tools behind premium subscription plans. They also tend to force customers into long-term agreements that don’t allow for much flexibility and charge hidden penalties for inadvertent use of unlicensed features.
AWS offers pay-as-you-go pricing, which means that costs scale with usage. As a result, database managers don’t have to worry about underestimating or overestimating resource needs. Instead, they can focus their energy elsewhere, knowing they’ll only incur fees for compute and storage their organization consumes. Cloud users can also upgrade or downgrade seamlessly, avoiding being locked into bad contracts.
AWS Databases: Modernized Architecture
Commercial database products tend to be monolithic by design. Services and applications often have to share a single database, making it hard to scale specific features, deploy updates, and make necessary schema changes. At a time when enterprise agility is essential, rigid commercial databases don’t fit the bill.
AWS databases, on the other hand, are designed to adapt to complex business requirements. Organizations can easily configure separate databases to support different microservices that enable use case-driven applications. Consequently, development teams can push updates to individual microservices, make schema changes without disrupting entire applications, and scale unique features without overconsuming compute resources.
AWS Databases: Reliability & Security
In the global economy, database downtime is not an option. Many commercial vendors struggle to keep databases up and running, especially at higher volumes with demanding applications. Moreover, it’s common to see commercial vendors charge users for access to top-tier security features rather than offer those capabilities out of the gates.
Compared to commercial databases, cloud-based databases are more reliable and secure. Cloud users can distribute databases across many availability zones, ensuring that redundancies exist for all data. Database managers can also implement network isolation, encryption at rest, and other security protocols to protect their organization’s data effectively.
Commercial databases are beginning to fall behind in terms of scalability, latency, and processing power. As data volumes grow, these platforms will have a harder time meeting the complex needs of fast-moving organizations. Leaders today must collect, analyze, and act in near real-time to stay ahead of the competition.
AWS databases offer microsecond to sub-millisecond latency for any volume of data and can scale as needed. Database managers who aren’t sure how much compute and storage they need can start small and grow slowly. Furthermore, AWS users can offload much of the backend administrative work that would otherwise steal engineering resources. For example, AWS takes care of server provisioning, patching, and backups independently, thus freeing data teams to invest in other areas.
Download The Guide to Migrating Legacy Databases to AWS
We recently published an eBook that dives further into why it makes sense to migrate legacy databases to AWS. In the guide, we introduce you to powerful managed AWS databases services, including Amazon Relational Database Service (RDS) and Amazon Aurora, and explain why they are so valuable for modern organizations.
We also share how ClearScale helps leaders optimize IT infrastructure around these modern database technologies. Every database migration project is different, which is why it’s important to have expert help along the way. Our team can evaluate your migration readiness, refactor IT infrastructure for optimal cloud performance, and set you up for long-term success.
Want to discuss your database needs with one of our cloud experts? Schedule a call.