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Techday NZ
11 hours ago
- Business
- Techday NZ
Hitachi Vantara named leader for object storage by GigaOm Radar
Hitachi Vantara has been identified as a Leader in the latest GigaOm Radar for Object Storage, in a report that assessed 22 prominent object storage vendors in terms of innovation, scalability, and their ability to address the evolving needs of modern data environments. The company's Virtual Storage Platform One Object (VSP One Object) was highlighted for its performance and new capabilities introduced since its release in late 2024. Of particular note is its industry-first native support for Amazon S3 Tables, allowing enterprises to conduct SQL-based analytics directly on object storage, and reducing reliance on traditional and more complex data pipelines. Recognition and features The GigaOm Radar for Object Storage evaluates vendors on factors such as innovation, platform readiness, reporting, and overall contribution to enterprise IT strategy. Within this context, Hitachi Vantara was recognised for its capabilities in reporting and analytics, storage optimisation, and public cloud integration. According to the report, object storage solutions such as VSP One Object are becoming increasingly significant to organisations managing exponential growth in unstructured data, including images, videos, IoT, and AI workloads. The GigaOm analysis underscores the value of performance, security, and edge readiness as key drivers for business and IT leaders when selecting storage solutions. Whit Walters, GigaOm Analyst, said: "Hitachi Vantara is a global technology provider whose strategy centres on the VSP One common data plane, designed to unify block, file, and object storage. Within this framework, Hitachi VSP One Object serves as an enterprise-grade object storage component, providing scalable, secure, and self-healing storage for diverse workloads like backups, archives, AI, and data analytics." Recognised under the Innovation/Platform Play quadrant, Hitachi Vantara was noted for delivering advanced reporting features that enable organisations to track usage patterns, monitor capacity trends, and forecast future needs. The solution also automates identifying redundant data and offers public cloud integration, including support for S3 Object Lock and S3 Tables. S3 Tables capability VSP One Object introduces the ability to perform SQL queries directly on object storage, which allows businesses to move unstructured data into structured tables and run analytics in a streamlined manner. This capability is considered a significant development for modern data lakehouse deployments, as it reduces the need for complex data movement, extraction, and loading traditionally associated with analytics on large datasets. Octavian Tanase, Chief Product Officer at Hitachi Vantara, said: "By enabling SQL queries directly on object storage, you eliminate the need for complex data pipelines and reduce infrastructure overhead, providing data lake simplicity with enterprise-grade power. These enhancements to the VSP One portfolio reflect our broader vision for the future of data infrastructure – one unified platform, with a single control plane of VSP 360, across a single data plane for block, file, object, SDS, and mainframe storage. By enabling a fully integrated view of data across your cloud and on-premises environments, we provide customers with the flexibility and scalability to achieve new heights for data availability in the age of AI." The architecture is built to support open data formats such as Apache Iceberg and automates complex tasks like compaction, snapshot management, and metadata cleanup, reducing operational overhead and allowing organisations to focus on data analysis rather than infrastructure management. Meeting modern data demands VSP One Object is positioned within the broader VSP One portfolio, which brings together block, file, software-defined storage, and object storage. Its purpose-built architecture is intended to support a diverse range of use cases, including data protection, long-term retention, edge computing, and real-time analytics. The upcoming release plans to enhance these capabilities further by offering support for VSP One Block NVMe-QLC and TLC flash-based storage, which is expected to deliver improved price and performance metrics for enterprises navigating increasing storage demands and cost pressures. Recent accolades The company recently received further industry acknowledgements, including the 2025 Fortress Cybersecurity Award for Data Protection from Business Intelligence Group, highlighting the VSP One Object platform. Additionally, Hitachi Vantara was recognised as a Leader and Fast Mover in GigaOm's Radar for High-Performance Storage Optimised for AI Workloads, as well as a Leader and Outperformer in the GigaOm Radar for Primary Storage.
Channel Post MEA
23-06-2025
- Business
- Channel Post MEA
GigaOm Radar Recognizes Hitachi Vantara As a Leader And Fast Mover In High-Performance Storage Optimized For AI Workloads
Hitachi Vantara has announced it has been named a Leader and Fast Mover in the 2025 GigaOm Radar for High-Performance Storage Optimized for AI Workloads. This marks the first iteration of this GigaOm Radar report in this category, and Hitachi Vantara's inclusion as a leader highlights the company's ability to deliver high-performance, enterprise-ready infrastructure to meet the complex demands of AI and machine learning workloads. The GigaOm Radar for High-Performance Storage Optimized for AI Workloads is a comprehensive evaluation of the advanced storage market for AI workloads management. Inclusion in this report requires solutions to meet foundational criteria, and vendors are evaluated based on the key capabilities and features of their offerings. Leaders are selected based on strong performance across both current capabilities and forward-looking innovation, including the ability to execute as well as feature completeness and future readiness, representing solutions that are mature and strategically aligned with evolving enterprise AI demands. Hitachi Vantara was recognized for its Hitachi iQ portfolio of AI-ready infrastructure solutions, securing positive ratings in several key areas, including: Quality of service and workload isolation: The report notes that 'Hitachi iQ offers world-class QoS and workload isolation capabilities.' Hitachi iQ delivers advanced workload isolation by combining file system-level policies with a flexible cluster architecture, allowing teams to effectively allocate resources for a consistent, reliable performance across high-priority AI/ML workloads – even in multi-tenant or shared environments. The report notes that 'Hitachi iQ offers world-class QoS and workload isolation capabilities.' Hitachi iQ delivers advanced workload isolation by combining file system-level policies with a flexible cluster architecture, allowing teams to effectively allocate resources for a consistent, reliable performance across high-priority AI/ML workloads – even in multi-tenant or shared environments. GPU-direct storage integration : The platform features optimized drivers that deliver significant performance benefits for AI and ML workloads by enabling streamlined data transfer between storage and GPU memory. : The platform features optimized drivers that deliver significant performance benefits for AI and ML workloads by enabling streamlined data transfer between storage and GPU memory. AI-optimized data layout and management: Hitachi iQ demonstrates intelligent and automated data placement across different storage tiers, including TLC/QLC NVMe flash storage for performance and density, as well as object storage. Additionally, the portfolio utilizes real-time monitoring and user-defined policies that is designed to support optimal performance and cost efficiency across different data patterns. 'What really stood out about Hitachi Vantara's offerings is the quality of service and the ability to isolate workloads,' said Whit Walters, field CTO and analyst at GigaOm. 'They've delivered a well-integrated, scalable platform in Hitachi iQ, backed by enterprise-proven storage. This combination gives organizations a powerful and flexible foundation for operationalizing AI at scale, especially as large-scale AI and GenAI workloads will require the ability to manage data and performance as demands continue to grow.' The report accentuates Hitachi Vantara's ability to innovate, citing collaboration with NVIDIA on the NVIDIA Data Platform on Hitachi iQ. Additionally, the report highlights the platform roadmap that includes new hardware and AI solutions, such as the Hitachi iQ M Series, announced in March 2025. It also highlights Hitachi Vantara's advanced integration with Virtual Storage Platform One (VSP One), enabling intelligent tiering between NVMe flash and object storage. 'AI isn't just pushing the boundaries of what infrastructure needs to do; it's completely redrawing them,' said Octavian Tanase, chief product officer at Hitachi Vantara. 'Our goal with Hitachi iQ is to give customers a high-performance foundation that removes complexity, accelerates outcomes, and adapts to whatever their AI journey requires next. By integrating Hitachi iQ with our VSP One platform, we're enabling a flexible, intelligent storage strategy that's ready for what's now and what's next.' The rating reflects the latest recognition for Hitachi Vantara technology. In May, the company won the Sustainable Technology Award at the Global Tech & AI Awards 2025 for advancing sustainable data infrastructure with its VSP One Block solution. And earlier this year, the company announced that GigaOm recognized it as a Leader and Outperformer in the GigaOm Radar for Primary Storage for its VSP One hybrid cloud data platform.
Techday NZ
19-06-2025
- Business
- Techday NZ
Hitachi Vantara named leader for AI storage in GigaOm Radar 2025
Hitachi Vantara has been recognised as a Leader and Fast Mover in the 2025 GigaOm Radar for High-Performance Storage Optimised for AI Workloads. The newly released GigaOm Radar report evaluates advanced storage platforms designed specifically for artificial intelligence (AI) workloads. This is the first time the report has assessed high-performance storage optimised for AI, and Hitachi Vantara's positioning underscores the company's capabilities in supporting enterprise-scale data requirements for AI and machine learning (ML). Report evaluation The GigaOm Radar for High-Performance Storage Optimised for AI Workloads reviews market solutions based on their key capabilities, foundational criteria, feature completeness, and readiness for future demands. Leaders in this assessment are noted for their maturity and strategic alignment with evolving enterprise AI needs, as well as their ability to execute at scale. Hitachi Vantara's placement as a Leader and Fast Mover was attributed to its Hitachi iQ portfolio, which provides AI-ready infrastructure solutions. The report highlighted several strengths, including quality of service (QoS) and workload isolation, GPU-direct storage integration and AI-optimised data layout and management. The report noted, "Hitachi iQ offers world-class QoS and workload isolation capabilities." By combining file system-level policies with flexible cluster architecture, Hitachi iQ enables effective resource allocation, supporting consistent and reliable performance for high-priority AI and ML workloads, even in multi-tenant or shared environments. The platform's GPU-direct storage integration was identified as another area of strong performance. Optimised drivers within Hitachi iQ support efficient data transfer between storage and GPU memory, enhancing outcomes for AI and ML workflows. Additionally, Hitachi iQ's data management strategy utilises intelligent placement across storage tiers, such as TLC/QLC NVMe flash storage for high performance and object storage for additional capacity. Real-time monitoring and user-defined policies are built in to balance performance and cost efficiency for varying data patterns. Industry commentary "What really stood out about Hitachi Vantara's offerings is the quality of service and the ability to isolate workloads," said Whit Walters, Field CTO and Analyst at GigaOm. "They've delivered a well-integrated, scalable platform in Hitachi iQ, backed by enterprise-proven storage. This combination gives organisations a powerful and flexible foundation for operationalising AI at scale, especially as large-scale AI and GenAI workloads will require the ability to manage data and performance as demands continue to grow." The GigaOm report also referenced ongoing collaborations including a partnership with NVIDIA on the NVIDIA Data Platform for Hitachi iQ, a partnership that adds to the capabilities of the platform. The roadmap for Hitachi iQ includes new hardware and AI solutions, among them the Hitachi iQ M Series, announced earlier in the year. Integration with the Virtual Storage Platform One (VSP One) enables further intelligent tiering between NVMe flash and object storage, providing additional flexibility and performance optimisation. Octavian Tanase, Chief Product Officer at Hitachi Vantara, commented on the recognition. "AI isn't just pushing the boundaries of what infrastructure needs to do; it's completely redrawing them," he said. "Our goal with Hitachi iQ is to give customers a high-performance foundation that removes complexity, accelerates outcomes, and adapts to whatever their AI journey requires next. By integrating Hitachi iQ with our VSP One platform, we're enabling a flexible, intelligent storage strategy that's ready for what's now and what's next." Ongoing awards This rating follows recent industry recognition for Hitachi Vantara. In May 2025, the company was awarded the Sustainable Technology Award at the Global Tech & AI Awards for its efforts in sustainable data infrastructure with the VSP One Block solution. Earlier in the year, GigaOm also recognised Hitachi Vantara as a Leader and Outperformer in the GigaOm Radar for Primary Storage, related to its VSP One hybrid cloud data platform. The GigaOm Radar for High-Performance Storage Optimised for AI Workloads aims to shed light on platforms capable of addressing the increased performance, scalability, and operational requirements integral to enterprise AI and machine learning deployments.
