How to Achieve Cost-Efficiency Without Compromising Performance

In today’s cloud-driven world, organizations face an ongoing challenge: balancing cost-efficiency with top-tier performance. Enterprises using relational database workloads often encounter bottlenecks, such as high storage costs, sluggish processing speeds, or a lack of scalability to meet evolving demands, especially when preparing for the AI era.

The Problem with Traditional Architectures

Relational databases—whether Oracle, SQL Server, or PostgreSQL—are fundamental to enterprise operations. Yet, as workloads grow in complexity, traditional on-prem or native cloud solutions often fall short. High-performance requirements like low latency, rapid throughput, and scalability are crucial for modern applications but are difficult to achieve without incurring significant costs.

Take the example of a global asset management firm: after transitioning to the cloud, they found their system unable to meet performance benchmarks. With existing solutions failing to deliver, they needed an innovative approach to optimize both cost and performance while supporting their AI goals.

Unlocking the Power of AI with Silk

The answer lies in reimagining cloud infrastructure. Silk, a platform for high-speed software-defined cloud storage for AI, enables businesses to unlock the full potential of their relational database workloads. Here’s how Silk helps organizations meet their cost and performance needs:

• Cost Optimization: By reducing compute and licensing footprints, Silk enables enterprises to use smaller virtual machines while still achieving superior performance.

• Performance Gains: Silk consistently delivers low latency and high throughput, surpassing even advanced on-premises systems like Exadata.

• Effortless Scalability: Using Silk’s zero-footprint cloning, organizations can create multiple environments for development, testing, and AI modeling without duplicating storage costs.

• AI-Readiness: As AI agents become central to enterprise operations, Silk ensures the infrastructure can handle data-intensive tasks like real-time analytics and modeling.

The Path Forward

As businesses integrate AI into their workflows, ensuring robust, cost-efficient infrastructure is critical. Innovations like Silk’s software-defined cloud storage for AI simplify this process, enabling organizations to achieve their goals without the chaos of inefficiencies.