Top 5 Data Infrastructure Trends to Watch in 2026

Carlo Finotti
DataStrike

IT organizations are preparing for 2026 with increased expectations around modernization, cloud maturity, and data readiness. At the same time, many teams continue to operate with limited staffing and are trying to maintain complex environments with small internal groups. These conditions are creating a distinct set of priorities for the year ahead.

The DataStrike 2026 Data Infrastructure Survey Report, based on responses from nearly 280 IT leaders across industries, points to five trends that are shaping data infrastructure planning for 2026.

1. Rising Budgets Are Not Resolving Operational Gaps

According to the survey, 74% of IT leaders expect their budgets to increase in 2026. This indicates a strong organizational interest in improving infrastructure and addressing long-standing needs. However, the survey also shows that greater funding does not necessarily translate into expanded internal capacity.

More than half of respondents report that they still lack the internal resources needed to address issues promptly or support initiatives that require sustained technical focus. Database administration is a clear example. Only about one third of organizations employ dedicated database administrators (DBAs), and many of those teams consist of only one or two people responsible for managing a range of platforms, including Oracle, SQL Server, PostgreSQL and cloud-native environments. Because the average DBA salary exceeds $100,000, building larger internal teams is not always cost-effective.

As a result, many organizations are entering 2026 with more financial support but without the personnel required to fully leverage it. This imbalance is shaping technology choices, modernization timelines and the degree to which teams must rely on outside support.

2. Legacy System Modernization Is a Central Priority for 2026

The survey identifies modernization of legacy systems as the top challenge for 2026, with 46% of IT leaders selecting it as their primary concern. This indicates a shift from last year's focus on tool sprawl and adoption patterns. Modernization is now viewed as a prerequisite for supporting current demands and future growth.

Legacy systems often anchor critical workflows, but their limitations can affect performance, scalability and integration with cloud-native or distributed architectures. The survey results suggest that organizations are preparing to address these constraints directly. Modernization efforts may involve platform updates, restructuring of data environments, or reconfiguration of underlying infrastructure to support more flexible and efficient operations.

The elevated focus on modernization also reflects broader pressures to support data-driven initiatives and to improve reliability as workloads grow larger and more varied.

3. Technical Debt Has Become a Significant Operational Burden

A total of 33% of respondents identify technical debt as a primary challenge for 2026. This indicates a growing awareness of the impact accumulated constraints have on day-to-day operations and long-term planning.

Technical debt in data infrastructure can involve outdated configurations, aging database versions, integration points that no longer align with current workflows or architectural decisions that limit scalability. The presence of technical debt affects issues ranging from performance and availability to the ability to adopt new platforms or support emerging workloads.

According to the survey, more IT leaders recognize that unresolved technical debt can slow modernization, complicate cloud operations, and limit the effectiveness of new initiatives. As a result, addressing technical debt has shifted from a background task to a more deliberate component of planning for 2026.

4. Data Strategy Development Is Now a High-Priority Infrastructure Task

The survey shows that 61% of IT leaders rank development of a data strategy as their top priority for the coming year. This signals a broader shift in how organizations view the role of data planning within infrastructure management.

A data strategy encompasses decisions about data models, governance, lifecycle management, workload placement, integration patterns, and the use of cloud or open-source platforms. The report notes increasing adoption of open-source databases such as PostgreSQL as organizations work to reduce dependency on proprietary systems and manage costs more effectively.

As AI-related workloads grow in prominence, many organizations are reassessing how prepared their data environments are to support them. The emphasis on data strategy reflects the need for more coherent and better-aligned foundations before implementing large-scale changes or advanced analytics initiatives.

5. MSP Adoption Is Rising as Skill Requirements Expand

One of the most notable findings is the continued rise in reliance on managed service providers. The survey reports that 60% of organizations now use MSPs for data infrastructure support. This represents more than double the rate reported in DataStrike's 2025 survey.

This trend indicates a systematic shift in how organizations are filling skill gaps and managing increasingly diverse environments. MSPs are being used to offset staffing limitations, extend coverage across more platforms, or maintain systems that require specialized expertise. For many organizations, external support is becoming an integral component of their operating model as internal teams remain small. This trend is likely to grow as technologies are changing at a faster rate than what occurred over the last 5 - 10 years.

The report shows that organizations are planning for a year defined by modernization requirements, greater attention to data strategy, and increased dependence on external expertise. While budgets are growing, staffing limitations continue to shape what internal teams can realistically support. As a result, the most significant work ahead involves balancing investment with structural constraints and ensuring that data environments are prepared for evolving demands.

Carlo Finotti is SVP of Delivery at DataStrike

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Top 5 Data Infrastructure Trends to Watch in 2026

Carlo Finotti
DataStrike

IT organizations are preparing for 2026 with increased expectations around modernization, cloud maturity, and data readiness. At the same time, many teams continue to operate with limited staffing and are trying to maintain complex environments with small internal groups. These conditions are creating a distinct set of priorities for the year ahead.

The DataStrike 2026 Data Infrastructure Survey Report, based on responses from nearly 280 IT leaders across industries, points to five trends that are shaping data infrastructure planning for 2026.

1. Rising Budgets Are Not Resolving Operational Gaps

According to the survey, 74% of IT leaders expect their budgets to increase in 2026. This indicates a strong organizational interest in improving infrastructure and addressing long-standing needs. However, the survey also shows that greater funding does not necessarily translate into expanded internal capacity.

More than half of respondents report that they still lack the internal resources needed to address issues promptly or support initiatives that require sustained technical focus. Database administration is a clear example. Only about one third of organizations employ dedicated database administrators (DBAs), and many of those teams consist of only one or two people responsible for managing a range of platforms, including Oracle, SQL Server, PostgreSQL and cloud-native environments. Because the average DBA salary exceeds $100,000, building larger internal teams is not always cost-effective.

As a result, many organizations are entering 2026 with more financial support but without the personnel required to fully leverage it. This imbalance is shaping technology choices, modernization timelines and the degree to which teams must rely on outside support.

2. Legacy System Modernization Is a Central Priority for 2026

The survey identifies modernization of legacy systems as the top challenge for 2026, with 46% of IT leaders selecting it as their primary concern. This indicates a shift from last year's focus on tool sprawl and adoption patterns. Modernization is now viewed as a prerequisite for supporting current demands and future growth.

Legacy systems often anchor critical workflows, but their limitations can affect performance, scalability and integration with cloud-native or distributed architectures. The survey results suggest that organizations are preparing to address these constraints directly. Modernization efforts may involve platform updates, restructuring of data environments, or reconfiguration of underlying infrastructure to support more flexible and efficient operations.

The elevated focus on modernization also reflects broader pressures to support data-driven initiatives and to improve reliability as workloads grow larger and more varied.

3. Technical Debt Has Become a Significant Operational Burden

A total of 33% of respondents identify technical debt as a primary challenge for 2026. This indicates a growing awareness of the impact accumulated constraints have on day-to-day operations and long-term planning.

Technical debt in data infrastructure can involve outdated configurations, aging database versions, integration points that no longer align with current workflows or architectural decisions that limit scalability. The presence of technical debt affects issues ranging from performance and availability to the ability to adopt new platforms or support emerging workloads.

According to the survey, more IT leaders recognize that unresolved technical debt can slow modernization, complicate cloud operations, and limit the effectiveness of new initiatives. As a result, addressing technical debt has shifted from a background task to a more deliberate component of planning for 2026.

4. Data Strategy Development Is Now a High-Priority Infrastructure Task

The survey shows that 61% of IT leaders rank development of a data strategy as their top priority for the coming year. This signals a broader shift in how organizations view the role of data planning within infrastructure management.

A data strategy encompasses decisions about data models, governance, lifecycle management, workload placement, integration patterns, and the use of cloud or open-source platforms. The report notes increasing adoption of open-source databases such as PostgreSQL as organizations work to reduce dependency on proprietary systems and manage costs more effectively.

As AI-related workloads grow in prominence, many organizations are reassessing how prepared their data environments are to support them. The emphasis on data strategy reflects the need for more coherent and better-aligned foundations before implementing large-scale changes or advanced analytics initiatives.

5. MSP Adoption Is Rising as Skill Requirements Expand

One of the most notable findings is the continued rise in reliance on managed service providers. The survey reports that 60% of organizations now use MSPs for data infrastructure support. This represents more than double the rate reported in DataStrike's 2025 survey.

This trend indicates a systematic shift in how organizations are filling skill gaps and managing increasingly diverse environments. MSPs are being used to offset staffing limitations, extend coverage across more platforms, or maintain systems that require specialized expertise. For many organizations, external support is becoming an integral component of their operating model as internal teams remain small. This trend is likely to grow as technologies are changing at a faster rate than what occurred over the last 5 - 10 years.

The report shows that organizations are planning for a year defined by modernization requirements, greater attention to data strategy, and increased dependence on external expertise. While budgets are growing, staffing limitations continue to shape what internal teams can realistically support. As a result, the most significant work ahead involves balancing investment with structural constraints and ensuring that data environments are prepared for evolving demands.

Carlo Finotti is SVP of Delivery at DataStrike

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