Skip to content
In a world where every click, transaction, and digital interaction leaves a trail, the ability to manage, protect, and scale databases defines the line between stagnation and corporate leadership.
According to IBM , our world generates approximately 2.5 quintillion pieces of data , and a staggering 90% of all data available today was created in the last three years. This colossal volume is not just a statistical curiosity: it exposes the speed and intensity with which businesses are producing and consuming data. The real challenge now is not generating information, but knowing where and how to store it securely and quickly.
And this is where the story gets interesting. Much of this informational wealth isn't born in state-of-the-art solutions. It resides in ERP systems that have been operating for decades, relational databases that have undergone countless upgrades, and, in some cases, critical applications that no one dares to shut down. And this is understandable; after all, replacing everything at once would be expensive, risky, and potentially disastrous .
However, there is a safer path : the cloud. When well planned, it allows you to modernize your database infrastructure without dismantling what keeps your company afloat.
Throughout this article, we'll show you how this transition can be made safely, efficiently, and with a forward-looking vision , and how Skyone helps companies take this step, evolving without sacrificing what already works.
Enjoy!
2. The transformation in the role of databases
There was a time when databases were fixed structures, hosted on local servers, with restricted access and well-defined functions: recording, storing, and, when requested, delivering information. This model served a scenario of slower decision-making and predictable processes .
With the digitalization of businesses, databases took on a broader role. They began to support ERPs, CRMs, and other integrated systems, connecting departments and enabling complex operations. Even so, they remained limited in flexibility and speed .
Today, the landscape is different. According to Nutanix 's Enterprise Cloud Index , nearly 90% of organizations already use containers for some of their applications, and 54% state that 100% of their systems are now containerized . In practice, this means that applications, including databases, are "packaged" in an isolated and portable way, allowing them to be moved between different environments, scaled almost instantly, and updated without disrupting the rest of the operation.
This shift accelerated the transition of databases from static repositories to dynamic, scalable components integrated into modern infrastructure. Now, they need to deliver information in real time, ensure security from the source, and connect to automation and artificial intelligence (AI)
pipelines In this scenario, deciding where and how to host a database has become a strategic decision. More than choosing a technology, it's about defining the management and operational model that will support the company's growth—and it's these options that we'll discuss next.
3. Possible ways to host and manage databases
As the role of databases has evolved, the question has shifted from simply " which technology to use? " to " which combination of technology and architecture will support my business now and in the future? " This shift in mindset stems from a reality in which data needs to be available anytime, anywhere, integrated with existing systems and ready to scale as demand demands.
It's no longer about choosing an off-the-shelf solution, but about designing an ecosystem capable of combining stability and innovation . This involves deciding on the most appropriate database type, understanding how it behaves under different workloads, and, most importantly, choosing the right environment for it to operate securely and efficiently.
To make this decision, it's worth understanding the main types of databases and possible hosting environments.
3.1. Relational and non-relational databases
Relational databases (SQL) emerged in an era when predictability was synonymous with efficiency . Everything was organized in interconnected tables, like a giant jigsaw puzzle where each piece had its exact place. This discipline ensures complete record integrity and remains irreplaceable in systems that cannot afford errors, such as ERPs, financial platforms, or logistics controls. Here, reliability isn't a differentiator: it's a matter of operational survival.
Non-relational databases (NoSQL), on the other hand, emerged as a response to a much less predictable world . Designed to handle data arriving in irregular waves, from multiple sources and formats, they are like a workshop always ready to receive pieces of different sizes and shapes. They store everything from documents and images to data generated by IoT sensors or social media interactions. Their flexibility and near-instant scalability make them the foundation of applications that need to grow quickly and respond without delay, ranging from marketplaces streaming platforms .
More than a technological choice, choosing between a relational and non-relational database is about deciding how the business will react to changes, how it will integrate new information sources, and how quickly it will respond to market opportunities.
However, the storage format is only part of the equation: it's also important to consider the database's purpose and the range of models it needs to support—and that's where analytics and multi-model capabilities come in.
3.2. Analytical and multi-model databases
While relational and non-relational databases differ in how they structure and store data, analytical and multi-model databases differ in how they use this information and their ability to handle different formats in the same environment. And it's worth emphasizing: these categories are not mutually exclusive. An analytical database can be relational, and a multi-model database can contain both relational and non-relational data.
Analytical databases are, in essence, the company's "intelligence center ." A data warehouse , for example, can gather years of sales records from a retail chain, cross-referencing them with inventory and customer behavior data to predict demand and adjust prices. A data lake, , can store, side by side, security camera footage, PDF reports, and IoT sensor records from a manufacturing plant, all ready to be processed by AI algorithms or trend analysis.
Multi-model databases, on the other hand, are like a data "condominium" : different formats coexisting in the same space, each with its own function. Imagine a logistics company that stores routes and schedules in relational tables, digitized contracts as documents, and connections between suppliers and carriers in graphs—all in the same database, without the need for complex integrations.
Understanding these possibilities is important because cloud modernization isn't just about moving data to another server. It's about creating an architecture capable of handling multiple formats, different purposes, and future needs . And this architecture needs to be supported by the right hosting environment.
3.3. Hosting environments
After defining the format and purpose, we come to another crucial decision: in which environment these databases should run to consistent security, performance, and scalability
- The public cloud's main strength lies in its ability to scale up or down in near-real time. It's an ideal model for applications that need to respond to sudden changes in demand or for companies that prioritize agility in delivering new services. However, this freedom requires careful consideration of costs and security policies, as the infrastructure is shared .
- The private cloud follows a different logic: it's a dedicated environment, tailored to meet specific requirements, whether for compliance or integration with systems whose architecture cannot be changed. It's often chosen by organizations that cannot allow critical data to escape their control ;
- Hybrid and multi-cloud strategies are intentional: each application or database is placed in the environment that best serves its function. Sensitive operational data can be stored in a private environment, while an data lake runs in the public cloud to leverage on-demand processing power.
More than just deciding where to run it, this choice defines how each database will respond to the real demands of the business . For example, in a retail company with a high volume of online , hosting a critical relational database in an environment that doesn't guarantee low latency can mean abandoned carts and lost revenue. Conversely, a multi-model database that consolidates logistics, contract, and route data can gain a competitive advantage by running in an environment that allows simultaneous queries by different teams without performance drops. It is at this level of impact that the decision about the environment is reflected, that is, not only in the infrastructure, but in day-to-day results .
This combination of database type, purpose, and hosting environment paves the way for exploring the cloud's full strategic potential. These choices yield the benefits that truly matter to the business, translating into greater agility, intelligence, and security. In the next section, we'll show you how this works in practice!
4. What are the strategic benefits of the cloud for corporate databases?
After understanding the different types of databases and possible hosting environments, it's time to talk about what really matters: what concrete results these choices can bring . The cloud isn't just a place to store data, but rather an enabler of speed, intelligence, and business resilience.
Next, we'll see how this technology translates into strategic benefits for companies looking to go beyond the basics and transform their databases into high-value assets.
4.1. Availability and secure access from anywhere
In today's globalized landscape, where teams operate across time zones and customers demand instant responses, the ability to access data without geographic barriers has gone from being a differentiator to a fundamental requirement.
The cloud enables databases to be securely accessed and updated by authorized users from any connected device. This is orchestrated by robust mechanisms such as multi-factor authentication, end-to-end encryption, and centralized permissions management . The result is operational synergy: sales, operations, and customer service teams operate based on unified, real-time information, eliminating the need for unstable VPNs or manual synchronization processes.
4.2. Scalability according to demand
Today, the pace of business is unpredictable , and data consumption reflects this volatility . Demand spikes driven by promotions, seasonality, or unexpected events can multiply transaction volume in a matter of minutes.
The cloud offers elastic scalability , allowing instant resource adjustments, up or down, with a pay-per-use model. Imagine Black Friday for an e-commerce site : the database can support millions of simultaneous queries during the sales frenzy and return to normal consumption shortly thereafter, without the need to maintain idle infrastructure year-round.
4.3. Integration with data pipelines
An isolated database, no matter how secure, is an underutilized asset. Migrating to the cloud unlocks its true potential, enabling native integration with data pipelines Business Intelligence machine learning platforms , and automated workflows.
algorithms that adjust inventory in real time, or sensor data can trigger preventive maintenance before a failure occurs. This integration is intrinsic to the cloud environment, middleware complexity and accelerating the transition from data collection to strategic action.
4.4. Built-in security and compliance
The fear that data stored "in-house" is more secure than in the cloud still persists, but the reality is different. Today, leading cloud providers invest in security on a scale that most companies couldn't replicate . This ranges from end-to-end encryption and 24/7 monitoring to AI-based intrusion detection and automatic security patch
Furthermore, the infrastructure is designed to adhere to compliance standards such as LGPD, ISO 27001, and PCI DSS, simplifying audits and mitigating the risk of penalties. This means security is no longer an isolated effort and becomes a structural element of the operation.
4.5. Business continuity with advanced backup
Even with advanced preventive measures, failures and incidents are inevitable. This is where resilience becomes crucial.
In the cloud, backups can be automated and distributed geographically, ensuring that critical data remains accessible even in the face of physical disasters or cyberattacks. Disaster Recovery Plans (DRPs ) can be activated in minutes, restoring systems to the last safe point with minimal disruption. This transforms unforeseen events into mere temporary deviations, avoiding prolonged downtime or irreversible losses.
Ultimately, all these benefits have one thing in common: they increase a company's ability to react and adapt without losing control over its data. And it's not just about greater speed or security, but about gaining the freedom to evolve the infrastructure according to the pace of business.
This flexibility, however, only holds true when there is a method . This is where best practices come in, not as a formality, but as a guarantee that each decision in the migration to the cloud truly contributes to the expected result, as we will explore below. Keep following!
5. Best practices to start the modernization journey
Modernizing databases isn't simply about "moving existing data to the cloud." It's an opportunity to reevaluate the role this data plays in the business and redesign how it will be managed in the coming years.
For this change to yield real benefits, the process needs to be planned, with decisions based on information, not impulse. A structured and progressive path helps reduce risk and extract value from the very beginning:
- Understand the starting point : Before discussing the cloud, you need to thoroughly understand the current landscape, including which databases exist, which applications depend on them, where the bottlenecks are, and what technical or contractual constraints exist. This mapping prevents old problems from simply being relocated;
- Set meaningful goals : "Improve performance" or "reduce costs" are vague intentions. You need to translate the objective into measurable targets, such as response time, availability rate, or integration with specific analytics tools.
- Assess the total cost, not just the server price : migrating involves licenses, integration redesign, potential application updates, and team training. Anticipating these costs reduces the chance of going over budget mid-project;
- Choose the right migration approach : Reproducing what exists in the cloud (also known as lift-and-shift ) can be faster, but it doesn't always solve performance or scalability issues. In some cases, refactoring or replatforming yields better results, even if it requires more time;
- Define where each component will run : public, private, hybrid, or multi-cloud aren't purely technical choices. They define responsiveness, compliance with standards, and even the speed of launching new products.
- Configure security before migrating : Encryption, authentication, auditing, and access control aren't "finished business." If they aren't defined from the outset, they can slow down operations or expose sensitive data.
- Test like you mean it : Running pilots in a controlled environment helps validate performance, compatibility, and scalability. Discovering a bottleneck after the migration is much more expensive;
- Migrate in a controlled manner : dividing the process into stages, prioritizing less critical systems, allows you to adjust the plan according to the results and reduce the impact on the business;
- Prepare those who will operate and use it : A modern infrastructure is useless if users and administrators continue to behave as they did in the previous model. Therefore, training and process adaptation are part of the delivery process;
- Continuously pursue improvements : Once in the cloud, optimization is ongoing. You need to continually adjust parameters, integrate new tools, and review consumption to ensure your investment continues to pay off.
Following this logic prevents migration from being merely a digital relocation. Each decision is connected to a concrete objective , such as shortening the response time of a critical application, freeing up the IT team for more strategic tasks, or enabling previously impossible integrations.
When the process is conducted this way, the result is not just a database running in the cloud: it's an operation capable of handling peak demand without collapse , incorporating new data sources quickly, and maintaining security as a structural requirement, not a patch.
It's this alignment between technical execution and business impact that Skyone strives to deliver. In the next section, we'll show you how we transform a set of best practices into a clear roadmap , with predictable deadlines, costs, and results.
6. How does Skyone enable modernization without changing systems?
Migrating databases to the cloud while maintaining active legacy systems requires precision. One wrong step can compromise integrations, cause slowdowns, or disrupt operations. That's why we follow a structured process to reduce risk and accelerate results .
We begin with a detailed diagnosis . We map which databases exist, how they connect, which applications depend on them, and where the bottlenecks are. This mapping guides all subsequent decisions.
Based on this, we define the most appropriate migration strategy — lift-and-shift , replatforming or partial refactoring. We evaluate business impact, execution time, and total cost to choose the best path. Our proprietary platform automates steps such as data replication, environment configuration, and security adjustments, avoiding errors and delays.
We perform the migration continuously, keeping data synchronized between the current and new environments until all testing is completed. This way, the transition occurs without interrupting sales, service, or critical processes. And after the migration, we continue with active monitoring, applying updates, adjusting resources, and ensuring stable performance, even during peak periods. We work with leading cloud providers and also with hybrid models.
This way, modernization ceases to be a risk and becomes a planned evolution , where we preserve what works, optimize what limits, and deliver an infrastructure ready for growth without constraints.
7. Conclusion
Migrating a database to the cloud isn't simply swapping one server for another: it's redesigning the foundation on which the business operates . When done methodically, this transition creates an environment that responds quickly to demands, maintains secure operations, and makes room for initiatives that previously seemed distant, such as real-time predictive analytics or integrations with new data sources.
Each modernization needs to be treated as a strategic project, not a upgrade . This means mapping the current landscape in depth, eliminating structural bottlenecks, and configuring the architecture to support business growth— without compromising systems that are already integrated and functioning . This way, the result will be not just a database in the cloud, but a more agile, resilient, and innovative operation.
In this context, an increasingly crucial resource is the data warehouse , which consolidates information from different areas and makes it available for more robust analysis and more informed decisions. If you want to understand how it can further expand the potential of your data strategy, check out our article " Data warehouse without mysteries: what it is, how it works, and why your company needs it."
FAQ: Frequently asked questions about cloud databases
Migrating, operating, and protecting databases in the cloud involves many technical and strategic variables, and it's natural to have questions before making decisions. Below, we've gathered straightforward answers to some of the most common questions , so you can understand the essentials even without reading the rest of this content.
1) Is it possible to migrate to a cloud database without stopping operations?
Yes. With the right strategy and tools, it's possible to keep the original database and the new cloud environment synchronized until the migration is complete. This way, the transition occurs in the background, without interrupting sales, service, or critical processes. This approach requires planning, upfront testing, and continuous monitoring to ensure there's no data loss or performance degradation.
2) What is the difference between backup and database?
The database is the active environment where information is stored, organized, and accessed for daily use by applications. A backup is a backup of this information, created to be used in the event of a failure, loss, or data corruption. In other words, the database is the operating system; the backup is the safety net. In the cloud, it's common to adopt backups to increase resilience.
3) How to ensure security in the cloud?
Cloud security starts with choosing a reliable provider that offers end-to-end encryption, multi-factor authentication, continuous monitoring, and compliance with regulations such as the LGPD. But it also depends on good internal practices, such as access management, periodic audits, and ongoing configuration and patch . Ideally, security should be part of the project from the outset, not an afterthought.
