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Navigating the Complexities of the Modern Database Landscape

Tushita Gupta
Head of Product Design
Redgate Software

In today's data-driven world, the management of databases has become increasingly complex and critical. The following are findings from Redgate's 2025 The State of the Database Landscape report.

Rising Concerns Over Data Security

One of the most significant findings of the report is the growing concern over data security and access controls. With 38% of IT teams expressing worries about managing different technologies securely, this marks a notable 12% increase from the previous year, exacerbated as new regulations come putting increased pressure to ensure sensitive data is secured.

Interestingly, 21% of respondents are hesitant to adopt more than one database type due to security and compliance issues, despite the potential advantages that multi-platform environments can offer.

Adoption of Multi-Platform Database Environments

Flexibility, cost savings, and the need to serve diverse use cases are driving nearly three-quarters (74%) of IT teams to use two or more database platforms. A notable 25% of respondents are managing more than four database platforms, a trend that underscores the need for robust database management strategies to ensure data consistency, security, and compliance.

The report also highlights the growing preference for versatile and scalable database solutions, reflecting the evolving demands of modern data-driven applications and the need for robust data management strategies.

Challenges in Database Management

The complexity of managing multiple database platforms is a significant challenge for IT teams. The report highlights that 68% of teams do not have formal processes in place to share best practices, increasing the likelihood of human error and security vulnerabilities. This lack of formal processes can exacerbate the risks associated with managing complex database environments.

The Importance of Testing and Security Practices

The proliferation of database types and the pressure to deliver applications and services swiftly make testing a core component of modern database management. However, 71% of organizations still rely on manual methods to create test data, a time-consuming and high-risk strategy. This has led to 25% of IT leaders expressing concern about the pressure on their teams to manage test data effectively.

Despite these challenges, there is a silver lining. Organizations are becoming more aware of data security measures, with only 14% now lacking an approach for handling sensitive data, a significant decrease from 35% in 2023. This growing awareness is a positive sign that organizations are taking steps to improve their data security practices.

Addressing the Skills Gap

One of the most surprising findings from this year's survey is the ongoing skills gap. The report notes that 44% of data professionals would like professional development opportunities to be provided weekly or monthly, but two-thirds (67%) cite lack of time as the main barrier to participating in training. Organizations need to prioritize professional development and recognize that the skills gap is a critical challenge. Ensuring that the right people are in place to manage data securely and compliantly in an increasingly complex and diverse technology estate is essential for data protection and business success.

The Impact of AI Adoption

Security concerns continue to shape business practices as organizations consider the benefits of AI adoption. While 69% plan to adopt AI capabilities in the next two years, concerns about AI usage in database management have risen sharply. 61% of respondents now cite data security and privacy as key concerns, up from 41% in 2023. This highlights the need for organizations to carefully consider the security implications of integrating AI into their database management processes.

Conclusion

As organizations navigate the complexities of multi-platform database environments, the emphasis on data security, compliance, and professional development remains paramount. By addressing these challenges head-on, organizations can better manage their data and ensure that they are well-positioned to succeed in an increasingly complex and data-driven world.

Tushita Gupta is Head of Product Design at Redgate Software

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Navigating the Complexities of the Modern Database Landscape

Tushita Gupta
Head of Product Design
Redgate Software

In today's data-driven world, the management of databases has become increasingly complex and critical. The following are findings from Redgate's 2025 The State of the Database Landscape report.

Rising Concerns Over Data Security

One of the most significant findings of the report is the growing concern over data security and access controls. With 38% of IT teams expressing worries about managing different technologies securely, this marks a notable 12% increase from the previous year, exacerbated as new regulations come putting increased pressure to ensure sensitive data is secured.

Interestingly, 21% of respondents are hesitant to adopt more than one database type due to security and compliance issues, despite the potential advantages that multi-platform environments can offer.

Adoption of Multi-Platform Database Environments

Flexibility, cost savings, and the need to serve diverse use cases are driving nearly three-quarters (74%) of IT teams to use two or more database platforms. A notable 25% of respondents are managing more than four database platforms, a trend that underscores the need for robust database management strategies to ensure data consistency, security, and compliance.

The report also highlights the growing preference for versatile and scalable database solutions, reflecting the evolving demands of modern data-driven applications and the need for robust data management strategies.

Challenges in Database Management

The complexity of managing multiple database platforms is a significant challenge for IT teams. The report highlights that 68% of teams do not have formal processes in place to share best practices, increasing the likelihood of human error and security vulnerabilities. This lack of formal processes can exacerbate the risks associated with managing complex database environments.

The Importance of Testing and Security Practices

The proliferation of database types and the pressure to deliver applications and services swiftly make testing a core component of modern database management. However, 71% of organizations still rely on manual methods to create test data, a time-consuming and high-risk strategy. This has led to 25% of IT leaders expressing concern about the pressure on their teams to manage test data effectively.

Despite these challenges, there is a silver lining. Organizations are becoming more aware of data security measures, with only 14% now lacking an approach for handling sensitive data, a significant decrease from 35% in 2023. This growing awareness is a positive sign that organizations are taking steps to improve their data security practices.

Addressing the Skills Gap

One of the most surprising findings from this year's survey is the ongoing skills gap. The report notes that 44% of data professionals would like professional development opportunities to be provided weekly or monthly, but two-thirds (67%) cite lack of time as the main barrier to participating in training. Organizations need to prioritize professional development and recognize that the skills gap is a critical challenge. Ensuring that the right people are in place to manage data securely and compliantly in an increasingly complex and diverse technology estate is essential for data protection and business success.

The Impact of AI Adoption

Security concerns continue to shape business practices as organizations consider the benefits of AI adoption. While 69% plan to adopt AI capabilities in the next two years, concerns about AI usage in database management have risen sharply. 61% of respondents now cite data security and privacy as key concerns, up from 41% in 2023. This highlights the need for organizations to carefully consider the security implications of integrating AI into their database management processes.

Conclusion

As organizations navigate the complexities of multi-platform database environments, the emphasis on data security, compliance, and professional development remains paramount. By addressing these challenges head-on, organizations can better manage their data and ensure that they are well-positioned to succeed in an increasingly complex and data-driven world.

Tushita Gupta is Head of Product Design at Redgate Software

Hot Topics

The Latest

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...