{"slug": "storage-news-ticker-26-may", "title": "Storage news ticker - 26 May", "summary": "Acceldata claimed its Autonomous Data & AI Platform signals \"the end of the data lakehouse era,\" arguing that lakehouse architecture designed for human access fails in the agentic era. AWS launched Amazon Redshift RG instances powered by Graviton chips, offering up to 2.2x faster performance at 30% lower cost per vCPU. Hudson River Trading expanded with Dell, standardizing on PowerScale for market data and opening an AI research data center in Norway built on the Dell AI Factory.", "body_md": "# Storage news ticker - 26 May\n\nTop chutzpah marks to Acceldata for claiming its Autonomous Data & AI Platform, which enables enterprises to autonomously run data analytics and AI agents with trust across their cloud, on-premises, hybrid, and sovereign environments, signals “the end of the data lakehouse era.” Databricks will be so, so worried.\n\nRohit Choudhary, Founder and CEO, Acceldata, said: \"The lakehouse architecture was built for human access. It broke in the agentic era. We started Acceldata with the conviction that enterprise data would never consolidate, that hybrid would be the durable reality and that the data and AI platforms must evolve to support it. In Europe, data sovereignty mandates are accelerating this shift, making hybrid-native, jurisdiction-aware architectures a board-level imperative, not a future consideration.”\n\n…\n\nAWS has launched Amazon Redshift RG instances - a new generation of Redshift powered by AWS Graviton chips that promises significantly faster analytics performance at a lower cost. Key highlights include:\n\n- Up to 2.2x faster performance than RA3 for data warehouse workloads, at 30% lower price per vCPU\n- Up to 2.4x faster performance for Apache Iceberg workloads and 1.5x faster for Apache Parquet\n- Integrated data lake query engine removes the need for Redshift Spectrum\n- Zero per-terabyte scanning fees, replacing Spectrum’s $5/TB charges with a more predictable pricing model\n- Migration possible in as little as 10–15 minutes with elastic resize and no application code changes required\n\nThis blend of speed, cost efficiency, and an integrated data lake query engine makes Redshift RG instances well-suited to handle the high query volumes and low-latency requirements of today’s analytics and agentic AI workloads.\n\n…\n\nIBM Business unit Confluent, which supplies data streaming SW, announced new capabilities in Confluent Intelligence and Confluent Cloud, with updates including:\n\n- Natural language tools for managing streaming operations\n- Built-in PII redaction in Flink SQL\n- Private connectivity to external models through Azure Private Link\n- A new data build tool (dbt) adapter for real-time pipelines\n\nSean Falconer, head of AI at Confluent, said: “Most AI projects fail before they reach a single customer because the data layer breaks down. Teams have the models and the mandate, but security risks and fragmented data stop them from shipping. We’re fixing that by making the streaming layer the foundation for secure, production-ready AI.”\n\n…\n\nHudson River Trading is a privately-held, global quantitative trading firm, algorithmic/HFT shop that trades across 200+ markets worldwide, and reportedly accounts for a meaningful chunk of US equity volume on any given day. It’s expanding with Dell on two fronts;\n\n- PowerScale - HRT is standardizing on PowerScale as the data foundation for the critical market data its quant research teams use for algorithm development, backtesting, and predictive pricing simulations. PowerEdge R-series handles the compute. We’re told the pitch is iterative, large-scale experimentation without the storage layer becoming the bottleneck, a real-world test of PowerScale in one of the most IO-sensitive verticals out there and a tangible proof point for PowerScale in the AI Data Platform in financial services.\n- AI research data center in Norway, built on the Dell AI Factory. HRT just opened a facility at Lefdal Mine Data Centers on Norway's west coast, a repurposed mine next to a cold fjord that pipes seawater in for cooling. Inside: Dell IRSS with direct liquid-cooled PowerEdge XE9685L servers (AMD EPYC), Nvidia HGX B200 accelerators, Dell/Nvidia Spectrum-X Ethernet. IT’;s designed for energy-efficient AI training at scale.\n\n…\n\nOptical archive developer [Ewigbyte](https://www.blocksandfiles.com/data-protection/2025/12/17/seeing-the-light-ewigbytes-optical-archive-storage-technology-and-strategy/1723143) has entered into a strategic partnership with Belgian startup Capsyra, combining photonic glass storage with a cryptographic governance and continuity layer designed around long-term data survivability.\n\n…\n\nPoland’s Alior Bank is moving hundreds of virtual machines to Red Hat OpenShift with Hitachi Vantara VSP One block storage, via CSI software, and additional VSP systems. It expects to lower virtualization costs by 60% while improving operational efficiency and resilience through a consolidated technology platform and a multi-site active-active architecture [Global-Active Device] designed for near-zero downtime. OpenShift will rum both VMS and containers. Read more [here](https://www.hitachivantara.com/en-us/company/customer-stories/alior-bank-customer-story ).\n\n...\n\nFast block storage supplier Lightbits has hired former Infineon VP Ramesh Chettuvetty to lead product and business for its AI solutions group, focused on [Inferra](https://www.blocksandfiles.com/ai-ml/2026/03/12/lightbits-and-scaleflux-demo-100x-to-280x-kv-cache-acceleration/5209158), the company’s KV cache acceleration engine aimed at reducing GPU stalls and scaling long-context inference for NeoCloud providers. Chettuvetty will drive the business forward and build the playbook for Lightbits’ AI solutions in the next generation of data centers and NeoClouds, ensuring that the company’s technology solves hardware efficiency and performance challenges faced by organizations running GPU-heavy workloads.\n\n…\n\nEuropean cloud service provider Elastx, a long-standing Lightbits customer, has extended its Elastx Cloud Platform (ECP) using Lightbits LightOS software-defined block storage, adopting an all-journaling architecture that replaces specialized Optane persistent memory (PMem) with standard NVMe SSDs. This architectural shift enables Elastx to:\n\n- Maintain sub-millisecond latency and high throughput\n- Improve resilience against node and power failures\n- Simplify hardware procurement and reduce supply chain risk\n- Reduce storage TCO\n- Scale infrastructure using commodity hardware\n\n…\n\nTrendForce reports Micron’s Fab 6 facility in Virginia, USA, has begun production of LPDDR4 and DDR4 DRAM using the 1α nm process. The LPDDR4 and DDR4 products manufactured at this fab will be shipped to clients in key application segments such as automotive electronics, industrial equipment, networking, medical devices, and defense and aerospace hardware. The expansion at Fab 6 mainly reflects Micron’s internal production capacity reallocation and does not indicate a renewed focus on supplying DDR4 components for consumer electronics.\n\n…\n\nNasuni, describing itself as a leading unstructured data platform for enterprise teams and AI, announced findings from its “The State of Enterprise File Data Annual Report 2026.” It reveals a widening gap between AI adoption and outcomes: 97% of organizations have deployed or are piloting AI agents, yet 57% of AI projects are not reported to be delivering their objectives. This shortfall is largely driven by data-related challenges, with nearly all enterprises (94%) struggling to manage unstructured data, which comprises the majority of their data footprint. While only 16% currently prioritize unstructured data management as a core IT investment, 60% plan to invest over the next 18 months, reflecting growing recognition of the role proprietary, operational data plays in driving desirable business outcomes with AI.\n\nNasuni talks about unstructured data but means file and not object data. Eg: “In 2026, file data is mission-critical for both people and the AI that supports them. How are organizations handling the explosion in unstructured data, to maximize business success?” It says that, with AI, there is a need to add semantic context to file data, and data management has to change and adapt to this. Semantic context means adding definitions, hierarchies, permissions, and more to indicate what the data represents (e.g., a contract's sensitivity, a design file's version history, or folder structures' intent).\n\nRequest a report copy [here](https://info.nasuni.com/state-of-enterprise-file-data-2026?_gl=1*mqcvk0*_gcl_aw*R0NMLjE3Nzk3ODUxNjguRUFJYUlRb2JDaE1Jby0tWHM4aldsQU1WQVpkUUJoMFNwejJORUFBWUFTQUFFZ0poVl9EX0J3RQ..*_gcl_au*MTQzMjgzNDYyNy4xNzc5Nzg1MTY1*_ga*MTgzNTczOTA3NS4xNzc5Nzg1MTY1*_ga_V1111WW8P9*czE3Nzk3ODUxNjYkbzEkZzEkdDE3Nzk3ODUyMjEkajEwJGwwJGgw).\n\n…\n\n…\n\nPeter Airs joined OWC (Other World Computing) in April as European Marketing Manager and is building up the company's European marketing presence, based in it existing EMEA operations.\n\n…\n\nData integrity supplier Precisely announced that EngageOne Compose and EngageOne Vault can now be deployed on Amazon Web Services (AWS). Regulated enterprises can run Customer Communications Management (CCM) directly within their own AWS environments, without re-platforming or moving data outside established governance boundaries. By keeping communications data governed and accessible within trusted cloud environments, this release helps organisations operationalise AI-driven communications, automation, and future customer engagement initiatives.\n\n…\n\nMulti-protocol, multi-media, storage supplier StorONE is announcing record first-quarter results, with Q1 bookings and revenue surpassing the company’s entire 2025 results. This is being driven by rapidly accelerating enterprise demand for StorONE’s Real-Time Tiering technology amid the ongoing flash and hardware supply crisis. StorONE also reported that average enterprise sales cycles shortened from approximately 4.5 months to 2.5 months, reflecting increasing urgency among organizations seeking immediate ways to lower storage costs and deploy infrastructure without waiting for constrained hardware supply chains.\n\n…\n\nTrendForce’s top five NAND supplier’s revenue ranking in Q1 2026 shows Samsung reinforcing its top supplier role and SK Hynix losing the most revenue share:\n\nIt says “CSPs worldwide experienced an exponential surge in demand for enterprise SSDs in 1Q26 due to the need for high-speed data transmission and the massive data storage capacities required to build out AI server infrastructure. Additionally, a persistent structural shortage of traditional HDDs has led a significant volume of storage-related orders to shift toward QLC enterprise SSDs.”\n\nWe’re told: ”NAND Flash suppliers generally anticipate continued growth in their shipments through the second quarter, and their pricing strategies are expected to sustain elevated ASPs.”\n\n…", "url": "https://wpnews.pro/news/storage-news-ticker-26-may", "canonical_source": "https://www.blocksandfiles.com/ai-ml/2026/05/26/storage-news-ticker-26-may/5246193", "published_at": "2026-05-26 13:48:20+00:00", "updated_at": "2026-05-26 14:13:04.155495+00:00", "lang": "en", "topics": ["ai-infrastructure", "ai-products", "ai-startups", "ai-agents"], "entities": ["Acceldata", "Databricks", "Rohit Choudhary", "AWS", "Amazon Redshift", "Graviton", "Apache Iceberg", "Apache Parquet"], "alternates": {"html": "https://wpnews.pro/news/storage-news-ticker-26-may", "markdown": "https://wpnews.pro/news/storage-news-ticker-26-may.md", "text": "https://wpnews.pro/news/storage-news-ticker-26-may.txt", "jsonld": "https://wpnews.pro/news/storage-news-ticker-26-may.jsonld"}}