Storage news ticker – April 9

Data protector Catalogic announced Catalogic DPX 4.15, the latest version of its all-in-one enterprise backup and recovery solution. This release introduces significant new features including full web-based NDMP management, tag-based VMware backup policies for more dynamic protection, and enhanced security capabilities including KMIP-based encryption key management and encrypted cloud archive support.

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Cloudera announced a raft of advances to its hybrid data platform, aimed at enhancing performance, flexibility, and data collaboration across modern data architectures. The update includes extended support until 2032 in addition to new capabilities such as: 

• Automated optimization of Apache Iceberg tables, powered by Cloudera Lakehouse Optimizer, which helps to accelerate query performance and reduce storage overhead.
• The ability to scale compute on demand with Cloudera Cloud Bursting, using cloud resources for peak workloads without moving data, improving utilization while maintaining security and governance.
• Expanded data sharing enables secure access to live Iceberg tables across external platforms without copying or duplicating data, reducing silos and preserving data integrity.

Cloudera is showcasing its latest platform capabilities this week at Iceberg Summit 2026.

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IDC conducted an in-depth analysis of customers of DataHub Cloud, the context management platform. Context management is the organization-wide capability to reliably deliver the most relevant and trusted data to AI context windows, enabling the governed and enterprise-scale deployment of agents. "Context" refers to the combination of structured metadata (schemas, lineage, quality metrics) and unstructured knowledge (documentation, business definitions, institutional expertise) that AI models need to make informed decisions. Findings include:

Data Engineering & Analytics Productivity

• Teams find data 91 percent faster (50 min to 5 min), 3x higher search success rate, driving 13-18 percent productivity gains across data engineering, analytics, and pipeline teams
• Analytics teams cut delivery time from 6-7 weeks to ~3 weeks
• 16 percent more searches are being conducted and a there has been a 51 percent increase in users leveraging natural language search using Ask DataHub so the platform drives broader adoption, not just speed

Data Quality & Incident Management 

• DataHub Cloud gives teams visibility into quality signals, ownership, and lineage so they can identify issues upstream, understand downstream impact, and fix them faster. Customers reported 56 percent fewer data completeness issues, 48 percent fewer timeliness issues, and cut outage resolution time by 58 percent

Governance & Compliance

• Scale without headcount growth with 20 percent governance team efficiency gains
• 8 percent compliance team efficiency gains, with auditable data controls for regulated industries. Without data visibility, compliance certifications are at risk. DataHub Cloud gives regulated industries a demonstrable, auditable record of how data is sourced, transformed, and consumed
• 153 percent more assets with complete metadata. 75 percent more datasets with mapped lineage

AI/ML Operationalization

• 119 percent more AI/ML models successfully reaching production
• 24 percent lower project failure rate. One of the biggest unlocks for AI is knowing your training data is trustworthy and traceable.. DataHub Cloud gives ML teams visibility into upstream data quality and lineage so they can catch issues earlier, move models to production faster, and fail less often

Data & Storage Cost Reduction

• 8 percent fewer storage costs on average. Customers reported saving $250K-$300K/year on storage by identifying redundant and unused data assets

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MRAM developer Everspin announced a strategic manufacturing agreement with Microchip Technology to expand production capacity and strengthen long-term supply. It’s entered into an initial ten-year agreement that can be extended in two-year increments, with Microchip Technology to augment its onshore manufacturing capacity for MRAM and Tunnel Magnetoresistive (TMR) sensor products. The company will establish a copy exact (plus) MRAM line to manufacture MRAM and TMR sensor products currently produced at its line in Chandler, AZ. 

Everspin and its customers get:

• Increased wafer capacity to support growth plans 
• On-shore second source for MRAM and TMR sensor products 
• Continuity of supply lasting well into the next decade

Everspin will retain ownership of the intellectual property and manufacturing process while utilizing Microchip’s foundry services capacity. Everspin will continue to manufacture MRAM and TMR sensor wafers in its Chandler, AZ facility co-located at NXP. 

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FUJIFILM North America Corp, Data Storage Solutions division, today announced availability in the United States of the FUJIFILM LTO Ultrium 10 (40 TB) Data Cartridge.

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Estonia-based Leil announced Leil OS, a storage operating system built from the ground up for Shingled Magnetic Recording (SMR) drives. Leil OS marks a strategic shift from hardware-agnostic storage software toward a purpose-built, HDD-native architecture designed to close the efficiency gap between hyperscaler storage operations and the broader enterprise market. As the only software stack purpose-built to fully support the industry’s most widely deployed, high-capacity, and cost-efficient HDDs, Leil OS establishes a new standard for HDD-native storage.

SMR drives have become a hard-drive standard for hyperscale and enterprise workloads, and Leil OS enables operators to harness them at near-raw hardware maximum speeds – unlocking up to 20 percent more capacity with no trade-offs. 

Leil’s proprietary Infinite Cold Engine (ICE) technology leverages the SATA/SAS Power Pin3 standard to physically disconnect electricity from idle HDDs – true zero-watt standby at a drive level. ICE manages power transitions at the filesystem layer, reducing electricity OPEX by up to 70 percent while keeping up to 90 percent of drives in a powered down state with a fast wake-up as necessary. More information here.

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NetApp announced its participation in a new marketing research study conducted by Callan Consulting, a Silicon Valley executive marketing consulting firm, joining 18 B2B and B2C technology companies to examine how AI is reshaping modern marketing organizations, marking a clear shift from early experimentation to embedded, enterprise‑wide adoption. The 2026 State of AI in Technology Marketing report highlights several notable changes since Callan Consulting’s prior study dated November 2024, including the emergence of “Born in AI” companies that built marketing organizations around generative AI from day one, the rapid expansion of AI use cases across the marketing lifecycle, and the growing importance of new disciplines such as Answer Engine Optimization (AEO) as customers’ buying patterns shift toward AI‑driven interfaces.

The report is available now from Callan Consulting here.

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Data integration supplier Precisely appointed Matt Waxman as chief product officer (CPO) to lead the company’s global product organization, overseeing product strategy, innovation, and execution of products, including the Data Integrity Suite, while also advancing initiatives supporting the company’s vision for agentic-ready data. Most recently, Waxman served as chief product officer at Arctera, where he helped lead the spin-out of the $400 million data management business from Veritas, and oversaw the company’s global product organization. He has held senior product leadership roles at Veritas, Cohesity, Puppet, and Dell EMC, where he led product strategy in data protection, SaaS platforms, and multi-cloud data management portfolios. 

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W. Curtis Preston and Michael Saylor have a new book: Learning Ransomware Response & Recovery: Stopping Ransomware One Restore at a Time, published by O’Reilly Media. This 485 page tome is quite the most thorough guide we have ever seen to ransomware attacks, stopping them, and recovery from such attacks.

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 Scale Computing and Nexsan have partnered to simplify virtualization with enterprise-grade external storage. The joint offering is claimed to be ideally suited for retail, healthcare, manufacturing, education, government and other edge-heavy sectors that need local application performance with centralized data strategies. Check out a solution brief on how the combination of SC//HyperCore virtualization suite and Nexsan’s external storage provides this here.

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The UK IBM Storage Scale User Group has confirmed dates for the 2026 meeting. It will run a dedicated New User Day ahead of the main conference, aimed at those newer to Storage Scale or looking to strengthen their foundational knowledge. Both events are now open for registration via Eventbrite: New User Day here and main conference here.

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StreamNative, a company founded by the creators of Apache Pulsar, one of the most widely used open-source data streaming platforms, announced a way to make every Kafka topic simultaneously a lakehouse table - no connectors, no ETL, no second copy of the data. It’s native Kafka, not Kafka-compatible. Their new engine, Ursa For Kafka (UFK), is an Apache Kafka 4.2+ fork - every existing client, tool, and connector works with zero code changes. Key Capabilities of Ursa For Kafka:

• Native Apache Kafka Protocol – Apache Kafka 4.2+ fork; every existing Kafka client, tool, and connector works with zero code changes
• Lakehouse-Native Storage – Every topic stored as Iceberg or Delta Lake tables on object storage; query streaming data from Spark, Snowflake, Databricks, and Trino
• Up to 95 percent Cost Reduction – Leaderless architecture eliminates cross-AZ replication, validated at 5 GB/s sustained throughput
• Zero-Connector Lakehouse Integration – No Kafka Connect, no materialization pipelines, no sink connectors; Kafka topics ARE lakehouse tables
• Catalog Integrations – Works with Databricks Unity Catalog, Snowflake Horizon Catalog, and AWS S3 Tables out of the box
• Mixed Storage Flexibility – Run cost-optimized (lakehouse-native) and latency-optimized (disk-based) topic profiles in the same cluster
• Available on AWS and GCP – With Azure expansion planned

For more information on UFK, read StreamNative’s blog post.

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The UALink Consortium announced the release of four new specifications:

 UALink Common Specification 2.0

• Introduces In-Network Compute for UALink technology, facilitating computation and communication between accelerators.
• Reduces latency, saves bandwidth, and improves scaling efficiency for distributed training and inference for AI solutions for complex and multi-workload environments for UALink systems.

UALink 200G Data Link and Physical Layers (DL/PL) Specification 2.0

• Split the DL/PL Specification from the UALink Common Specification to enable UALink to move quickly as new physical layers and speeds are needed by the industry without requiring changes to the other specifications.

UALink Manageability Specification 1.0

• Introduces UALink as a system with centralized control and management planes.
• Utilizes standardized protocols, modeling and APIs like gNMI, Yang, SAI and Redfish.

UALink Chiplet Specification 1.0

• Defines the necessary information to integrate UALink technology into chiplet-based SoCs, including interfaces, form factors, flow control and chiplet management standardization.
• Fully compliant with the UCIe 3.0 Specification for simplified integration into existing chiplet ecosystems.

All of the UALink specifications are available for public download here.

The Ultra Accelerator Link (UALink) Consortium, incorporated in October 2024, is the open industry standard group dedicated to developing the UALink specifications, a high-speed, scale-up accelerator interconnect technology that advances next-generation AI & HPC cluster performance. The consortium is led by a board made up of stalwarts of the industry: Alibaba, AMD, Apple, Astera Labs, AWS, Cisco, Google, HPE, Intel, Meta, Microsoft, and Synopsys. The Consortium develops technical specifications that facilitate breakthrough performance for emerging AI usage models while supporting an open ecosystem for datacenter accelerators.

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Virtana announced AI Factory Observability for Nutanix Agentic AI environments, extending system-aware observability across Nutanix Cloud Infrastructure and Nutanix Enterprise AI. It’s expanding AI Factory Observability from Nutanix Cloud Infrastructure into Nutanix Enterprise AI, extending visibility and control from the infrastructure layer into AI platforms and model-driven workloads. This integration provides infrastructure and platform teams with a shared operational foundation for managing Nutanix Agentic AI environments in production.