The Cost of Standing Still on Legacy Databases: How the New Era of Data Platforms Can Unlock Data & AI Innovation

Over recent times data platforms have taken enormous strides forward, yet as our data expert Julian Wise, Principal Technologist, warns, many organisations risk falling behind by clinging to outdated systems. As Julian has observed:

“Today, the organisations moving fastest are fundamentally changing how their data works for them with a cloud-connected approach, not just migrating for increased storage or cost effectiveness.”

The Low Down From Julian Wise: Why A Cloud-Connected Approach Unlocks Data & AI Innovation

With a cloud-connected approach, such as Azure’s intelligent data ecosystem optimised on Intel® Xeon® processors, organisations can access the latest AI, analytics, and governance tools, and these capabilities are increasingly essential for staying competitive and turning data into real business value.

Migrating to the cloud to adopt modern Data and AI solutions like Azure Database for PostgreSQL, unlocks access to AI Data Agents, governance frameworks, and analytics capabilities that can transform the way you interact with your information.

Combined with expert insights, these tools help organisations uncover new value from their data, sparking innovation and enabling smarter business decisions.

An Integrated, Open Solution That Eliminates Data Silos

Data and AI-powered digital transformation offers organisations the opportunity to accelerate growth and unlock savings.

“The Microsoft Azure Cloud and AI Platform provides an integrated, open solution that eliminates data silos, enabling a single view of the truth,” says Frederico Pravatta Rezende, Linux and open-source databases Partner Strategy Lead.

“This connected platform simplifies integration and operations, supports best-in-class solutions, and ensures built-in security, compliance, and intelligent automation. As a result, organisations can focus their investments on differentiated data products and applications that drive business value.”

The Hidden Costs of Legacy Systems

Legacy databases may appear cost-effective on the surface, but the hidden costs quickly add up. Beyond licensing fees, organisations are losing potential value by keeping data trapped in silos, with even well-implemented data lakes able to underperform if the information remains isolated. This, in turn, restricts insights, slows decision-making, and stifles innovation.

By updating these legacy systems, you allow for standardised reporting, ensure data is trusted, and provide controlled access through self-service and access control lists, unlocking efficiencies and insights that legacy systems simply cannot deliver.

Conversational Data at Enterprise Scale

Since the rise of tools like ChatGPT, AI in the enterprise has become more accessible than ever. Today, many organisations are using natural language to question their data, having real conversations with AI Agents to explore things like sales, revenue, or operational cycles. Platforms such as Azure AI make this even more achievable, provided the underlying data estate is modernised.

Data and AI Agents require context around your tables and columns, needing instructions on how to understand the data and interact with users. Once that context is provided, organisations can have meaningful conversations with their data, set up APIs, and run a series of queries that automate insights at scale.

Organisations that remain on outdated on-premises hardware are missing out on the full suite of productivity features, automation, and AI capabilities that modern cloud platforms and modern processors make possible, putting them at a real disadvantage.

“Intel’s commitment to open source and AI communities spans decades, and it continues to be the foundation for how we help customers modernise, securely and at scale. Together with LAB³, we’re accelerating adoption of PostgreSQL and other workloads that benefit from modernisation on Intel® Xeon® processors,“ says Brian Rogers, Solutions Architect at Intel.

“Active members of Intel’s community benefit from upstreamed optimisations, built‑in AI acceleration, and a robust ecosystem of tools that make AI‑ready databases practical in production.“

Brian continues to explain: “Just as important, we’re aligning those performance gains with enterprise‑grade security: Confidential Computing and related technologies help protect data in use while enabling innovative AI patterns across cloud and hybrid environments.”

Cloud Migration as a Strategic Shift

Cloud migration represents a strategic shift in how companies operate, innovate, and compete. Cost improvements often motivate migrations, especially when licensing periods come to an end, but the real value comes from scalability and access to modern capabilities.

Migrating Linux and PostgreSQL workloads to Azure with Intel® Xeon® processors, AI accelerators, and open-source tools enables faster product development, enhanced customer experiences, richer insights, and stronger security postures. For sectors like financial services and government, moving to the cloud helps organisations modernise and make the most of AI, which is becoming essential to staying competitive.

Governance and Security in the Modern Era

Regulatory compliance is a must in today’s business landscape, and a consideration at the top of leader’s lists across the country. Cloud-based platforms like Azure allow for column and row-level security, sensitivity labels across multiple databases, and full visibility over who is accessing what. When combined with the trusted execution capabilities and reliability of Intel® Xeon® processors, organisations gain an even stronger foundation for secure and compliant data operations.

Unlocking Automation and AI-Driven Workflows

Moving to the cloud unlocks immediate benefits for businesses, particularly when modernised on Azure with Intel architectures. These tools reduce engineering effort by curating datasets into practical business applications and ensuring streamlining workflows, making it easier to progress from basic reporting to driving decisions with AI.

Optimising performance on platforms like Linux and PostgreSQL on Azure allows organisations to scale efficiently, while maintaining cost effectiveness and flexibility.

The Real Cost of Standing Still

Staying on legacy databases carries real costs beyond license fees. Operational overhead increases as teams spend more time patching, maintaining, and managing aging infrastructure.

Security vulnerabilities and compliance risks rise as platforms age, while talent shortages make it harder and more expensive to maintain the right skillsets.

Integrating legacy systems with modern applications is often complex and fragile, and more importantly, it slows digital transformation, making it harder to adopt AI and cloud-native services that drive innovation.

Ultimately, standing still on legacy databases is expensive and the time to act is now. Migrating to the cloud, putting governance in place, and unlocking AI-driven data platforms aren’t optional, they’re essential to staying competitive. With the right guidance, training, and accelerators, organisations can move faster, more securely, and start realising the full value of their data.

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