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In a world where every click, transaction, and digital interaction leaves a trace, the ability to manage, protect, and scale databases defines the line between stagnation and business leadership.
According to IBM , our world generates approximately 2.5 quintillion data points , and an impressive 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 efficiently.
And this is where the story gets interesting. Much of this informational wealth does not originate from cutting-edge solutions. It resides in ERP systems that have been operating for decades, relational databases that have undergone numerous updates, 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 for the modernization of database infrastructure without dismantling what keeps the company afloat.
Throughout this article, we will show how this transition can be done safely, efficiently, and with a future-oriented vision , and how Skyone helps companies take this step, evolving without abandoning what already works.
Happy reading!
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: to record, store, and, when requested, deliver information. This model served well a scenario of slower decision-making and predictable processes .
With the digitization of business, databases have taken on a broader role. They have come to support ERPs, CRMs, and other integrated systems, connecting areas 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 in some of their applications, and 54% say that 100% of their systems are now containerized . In practice, this means that applications, including databases, are "packaged" in an isolated and portable way, and can be moved between different environments, scaled almost instantly, and updated without interrupting 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 real-time information, 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 point. More than choosing a technology, it's about defining the management and operation model that will support the company's growth—and it's about these options that we will discuss next.
3. Possible ways to host and manage databases
With the evolution of the role of databases, 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 change in mindset is the result of a reality where data needs to be available anytime, anywhere, integrated with existing systems and ready to scale as needed.
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 suitable type of database, understanding how it behaves under different workloads, and, above all, 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 the possible hosting environments.
3.1. Relational and non-relational databases
Relational databases (SQL) were born in an era where predictability was synonymous with efficiency . Everything was organized in interconnected tables, like a large jigsaw puzzle where each piece had its exact place. This discipline guarantees total record integrity and remains irreplaceable in systems that cannot afford to make mistakes, such as ERPs, financial platforms, or logistics controls. Here, reliability is not 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-instantaneous scalability make them the foundation for applications that need to grow quickly and respond without delays, ranging from marketplaces streaming platforms .
More than a technological choice, opting between relational and non-relational databases is about deciding how the business will react to changes, how it will integrate new sources of information, and how quickly it will respond to market opportunities.
However, the storage format is only part of the equation: it's also necessary to consider the purpose of the database and the range of models it needs to support—and that's where analytics and multi-model databases 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 are distinguished by how they use this information and their ability to handle different formats in the same environment. It's important to emphasize that 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 "intelligence center" of a company . A data warehouse , for example, can gather years of sales records from a retail chain, cross-referencing them with inventory data and customer behavior to predict demand and adjust prices. A data lake , can store, side-by-side, images from security cameras, PDF reports, and IoT sensor logs from an industry, 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. Accommodation environments
After defining the format and purpose, we arrive at another crucial decision: in what environment should these databases run to consistently deliver security, performance, and scalability
- In the public cloud , the main strength lies in the ability to scale resources up or down almost in 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. But this freedom requires increased attention to costs and security policies, since the infrastructure is shared .
- A private cloud follows a different logic: it's a dedicated environment, tailored to meet specific requirements, whether for compliance or integration with systems that cannot change their architecture. It's often chosen by organizations that cannot allow critical data to get out of control .
- Hybrid and multi-cloud on the other hand, are an intentional design: each application or database is placed in the environment that best suits its function. It is possible to keep sensitive operational data in a private environment, while an data lake runs in the public cloud to take advantage of 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 shopping carts and lost revenue. Conversely, a multi-model database that consolidates logistics, contracts, and routes 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 also in the day-to-day results .
This combination of database type, purpose, and hosting environment paves the way for exploring the full strategic potential of the cloud. From these choices arise the gains that truly matter to the business, translating into greater agility, intelligence, and security. In the next section, we'll show how this happens 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 is not just a place to store data, but rather a facilitator of speed, intelligence, and resilience in business.
Next, we'll see how this technology translates into strategic benefits for companies seeking 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 different time zones and customers demand instant responses, the ability to access data without geographical 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 permission management . The result is operational synergy: sales, operations, and customer service teams operate based on unified, real-time information, eliminating reliance on 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 for instant resource adjustments, both up and down, with a pay-as-you-go model. Imagine Black Friday for an e-commerce business : the database can handle millions of simultaneous queries during the sales frenzy and return to normal consumption shortly afterward, without the need to maintain idle infrastructure throughout the year.
4.3. Integration with data pipelines
An isolated database, however 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.
For example, sales records can be automatically routed to predictive algorithms that adjust inventory in real time, or sensor data can trigger preventative maintenance before a failure occurs. This integration is intrinsic to the cloud environment, eliminating the complexity of middleware and accelerating the transition from data collection to strategic action.
4.4. Built-in security and compliance
The fear that data kept “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 could not 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. Thus, security ceases to be an isolated effort and becomes a structural element of the operation.
4.5. Business continuity with backup and DRP
Even with advanced preventative measures, failures and incidents are inevitable. This is where resilience becomes crucial.
In the cloud, backups can be automated and geographically distributed, 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, preventing prolonged downtime or irreversible losses.
In the end, all these benefits have one thing in common: they increase the company's ability to react and adapt without losing control over its data. And it's not just about having more speed or security, but about gaining the freedom to evolve the infrastructure according to the pace of the business.
This flexibility, however, is only sustainable when there is a method . That's 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 reading!
5. Best practices to begin the modernization journey
Modernizing databases isn't simply about "moving existing data to the cloud." It's an opportunity to reassess 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 gains, the process needs to be planned, with decisions based on information, not impulse. A structured and progressive approach helps reduce risks and extract value from the very first steps.
- Understand the starting point : before discussing the cloud, it's necessary to thoroughly understand the current landscape, such as which banks exist, which applications depend on them, where the bottlenecks are, and what technical or contractual restrictions exist. This mapping prevents old problems from simply being transferred to another location.
- Define meaningful goals : "Improve performance" or "reduce costs" are vague intentions. It's necessary to translate the objective into measurable goals, such as response time, availability rate, or integration with specific analytical tools.
- Evaluate the total cost, not just the server price : migrating involves licenses, redesigning integrations, potential application updates, and team training. Anticipating these costs reduces the chance of exceeding the budget mid-project.
- Choose the right migration approach : replicating what exists in the cloud (also known as lift-and-shift ) may be faster, but it doesn't always solve performance or scalability issues. In some cases, refactoring or " replatforming " yields better results, even if it takes more time.
- Define where each component will run : public, private, hybrid, or multi-cloud are not purely technical choices. They define responsiveness, adherence to standards, and even the speed to launch new products;
- Configure security before migrating : encryption, authentication, auditing, and access control are not "finishing touches" to the project. If they are not defined from the beginning, they can delay operations or expose sensitive data.
- Test as if it were for real : running pilot projects in a controlled environment helps validate performance, compatibility, and scalability. Discovering a bottleneck after 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 act as in the previous model. Therefore, training and process adaptation are part of the delivery;
- Seek continuous improvement : once in the cloud, optimization is permanent. It's necessary to keep adjusting parameters, integrating new tools, and reviewing consumption, as this ensures the investment continues to pay for itself.
Following this logic prevents migration from being merely a change of digital address. 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 collapsing , incorporating new data sources quickly, and maintaining security as a structural requirement, not a patch.
This alignment between technical execution and business impact is what Skyone seeks to deliver. In the next section, we will show you how we transform a set of best practices into a clear roadmap , with predictable deadlines, costs, and results.
6. How does Skyone make modernization feasible without replacing systems?
Migrating databases to the cloud while keeping legacy systems active requires precision. One wrong step can compromise integrations, cause slowdowns, or interrupt operations. That's why we follow a structured process to reduce risks and accelerate results .
We start 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 assess 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, preventing errors and delays.
We perform the migration continuously, keeping data synchronized between the current and new environments until all tests are completed. Thus, the transition happens without stopping sales, customer 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 in hybrid models.
In this way, modernization ceases to be a risk and becomes a planned evolution , where we preserve what works, optimize what limits us, and deliver an infrastructure ready to grow without constraints.
7. Conclusion
Migrating a database to the cloud isn't simply about swapping one server for another; it's about redesigning the foundation upon which the business operates . When done methodically, this transition creates an environment that responds quickly to demands, keeps operations secure, and opens up opportunities 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 scenario in depth, eliminating structural bottlenecks, and configuring the architecture to keep pace with business growth— without compromising systems that are already integrated and functioning . In this way, the result will not only be a database in the cloud, but a more agile, resilient operation, prepared to innovate.
In this context, an increasingly crucial resource is the data warehouse , which consolidates information from different areas and makes it available for more robust analyses 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 made simple: what it is, how it works, and why your company needs it".
FAQ: Frequently asked questions about cloud databases
Migrating, operating, and securing databases in the cloud involves many technical and strategic variables, and it's natural for questions to arise before making decisions. Below, we've compiled direct 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 interrupting 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 happens in the background, without interrupting sales, customer service, or critical processes. This approach requires planning, prior testing, and continuous monitoring to ensure there is no data loss or performance degradation.
2) What is the difference between a backup and a database?
The database is the active environment where information is stored, organized, and accessed for daily use by applications. A backup , is a security copy of this information, made to be used in case of failure, loss, or data corruption. In other words, the database is the operational system; the backup is the safety net. In the cloud, it is common to adopt backups to increase resilience.
3) How to ensure security in the cloud?
Cloud security begins with choosing a reliable provider that offers end-to-end encryption, multi-factor authentication, continuous monitoring, and compliance with regulations such as the LGPD (Brazilian General Data Protection Law). But it also depends on good internal practices, such as access management, periodic audits, and constant updates of configurations and patches . Ideally, security should be treated as part of the project from the beginning, and not as a later adjustment.
