Compare Oracle Real Application Clusters (RAC) vs. Hammerspace

Oracle Real Application Clusters (RAC)

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What is Oracle Real Application Clusters (RAC)?

Oracle Real Application Clusters (RAC) is a unique and robust database architecture that provides exceptional availability and scalability for both read and write operations across a wide range of workloads, including OLTP, analytics, AI data, SaaS applications, JSON, batch processing, text, graph data, IoT, and in-memory tasks. It efficiently manages complex applications, such as those from SAP, Oracle Fusion Applications, and Salesforce, while ensuring outstanding performance. By employing a specialized fused cache shared among servers, Oracle RAC guarantees rapid local data access, resulting in low latency and high throughput for various data needs. The architecture's capability to parallelize workloads across multiple CPUs enhances overall throughput, and Oracle's advanced storage solutions allow for seamless online expansion of storage. Unlike traditional databases that depend on public cloud infrastructure, sharding, or read replicas to improve scalability, Oracle RAC distinguishes itself by delivering top-tier performance with minimal latency and maximum throughput right from the outset. Additionally, this architecture is crafted to adapt to the shifting requirements of contemporary applications, rendering it a forward-thinking solution for businesses aiming for longevity and efficiency in their database operations. Its design not only ensures reliability but also positions organizations to tackle future challenges in data management effectively.

What is Hammerspace?

Hammerspace is an innovative storage solution that unlocks the vast amounts of fast local NVMe storage inside GPU servers, turning what was previously stranded capacity into a new ultra-fast storage tier that accelerates AI training and checkpointing. Designed to overcome the limitations of expensive and complex legacy storage systems, Hammerspace enables consistently high GPU utilization by providing low-latency, parallel access to data across thousands of servers simultaneously. The platform’s global data architecture is built on standard NFS protocols, eliminating the need for proprietary clients and simplifying integration with existing Linux storage servers and hybrid cloud environments. By orchestrating data movement between on-premises and cloud infrastructure, Hammerspace supports flexible AI workflows that maximize resource usage and minimize power consumption. Hammerspace has been proven through MLPerf benchmarks to deliver scalable, linear performance gains, dramatically speeding up checkpointing times by 10 to 100 times. Trusted by industry leaders like Meta and Los Alamos National Laboratory, it helps reduce external storage costs, power usage, and rack space requirements. The platform’s intuitive interface and rapid deployment allow organizations to bring petabytes of capacity online within days and start accelerating AI workloads immediately. Its hyperscale NAS architecture ensures consistent throughput and low latency at scale, critical for large machine learning projects. By transforming idle GPU server storage into a shared, protected resource, Hammerspace redefines cost efficiency and performance in AI infrastructure. This technology empowers data-driven organizations to innovate faster, reduce their energy footprint, and optimize their AI investment returns.