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Insights From Analytics: Simplifying Data Management: Key Takeaways from the 53rd IT Press Tour

Purpose-Built for AI/ML Demands: Customers report slashing development cycles by over 90% by orchestrating AI/ML data flows with SupremeRAID™.

by Tom Smith for Insights From Analytics / Feb. 22, 2024

Data volumes are exploding across enterprises, straining infrastructure and threatening to overwhelm developers and engineers. Traditional management approaches struggle to keep pace with changing architectures and massive growth. Fresh thinking around specialized hardware, software intelligence, and cloud interoperability aims to ease these burdens.

Promising innovations arrived at the 53rd IT Press Tour, where I met startups tackling aspects of the data onslaught. While their approaches differed, common themes emerged around eliminating bottlenecks, integrating diverse infrastructure, and automating intensive management tasks.

Accelerating Performance

Groq’s specialized large language processing units maximize real-time AI inference throughput for interactive apps like chatbots. Graid‘s SupremeRAID harnesses GPUs to deliver uncompromising NVMe SSD speeds while safeguarding data. Both exemplify domain-specific silicon overcoming constraints to accelerate innovation.

Abstracting Infrastructure Complexity

Hammerspace, Rimage, and StorageX apply software abstraction to unify data access across infrastructure silos. Their platforms create unified layers spanning on-premise and multi-cloud resources while efficiently coordinating movement behind the scenes. This simplifies management and avoids fragmented user experiences.

Infusing Analytics with AI Assistance

CloudFabrix integrates data pipelines from across stacks, leveraging machine learning to pinpoint anomalies in cross-domain application and infrastructure interdependencies. HYCU taps natural language models to accelerate building data protection connectors and advise administrators. Cerabyte uses simulations to optimize policies for its glass-based archival storage.

Purpose-Built for AI/ML Demands

Hammerspace and Graid optimize solutions explicitly for surging AI/ML workloads. Key capabilities include accelerated data pipelines, unified data lakes, and cross-tier storage attuned to each stage of model development. By orchestrating AI/ML data flows, customers report slashing development cycles by over 90%.

Standards-Based Integration and Extensibility

Shared themes around integration, interoperability, and extensibility also stood out across vendors. Graid, Groq, Hammerspace, and others underscored support for platform-agnostic environments like PyTorch, open formats like Apache Arrow, and partnerships with major server and storage vendors to ease deployment. Extensible architectures enable customizable enhancements over time.

Additional Innovations

AirMettle integrates analytics directly into its software-defined object storage system, accelerating SQL queries up to 100X by bypassing unnecessary data movement. Its ability to handle diverse data types provides flexibility beyond structured warehouses. CloudFabrix overlays intelligent workflow automation onto its observability data pipeline. Software-defined storage specialist Rimage highlighted optical media innovations to cut cold storage costs by over 70% while supporting vital long-term data retention needs.

The innovations showcased indicate the data infrastructure space is entering a new era, with specialized hardware, software intelligence, and interoperability easing management burdens. While disruption won’t happen overnight, the progress exemplified deserves attention for its potential to help developers, engineers, and architects thrive amidst data explosions ahead.

Read the article on Insights From Analytics

Also see: Simplifying Data Management From Desktop to Datacenter With Graid Technology


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