VAST Data Delivers the First Fully Unified AI Data Platform, Adding Native Block Storage
VAST Data, the AI data platform company, recently announced new capabilities that deliver on VAST’s mission to provide a truly unified data platform for the AI era. Available next month, VAST has added Block storage functionality, completing the initial vision for the VAST DataStore as a universal, multiprotocol storage platform.
The VAST Data Platform, which seamlessly combines storage, databases, and virtualized compute engine services into a unified AI operating system, is now the only exascale solution on the market capable of linearly scaling parallel data access performance for every type of data – file, object, block, table, and streaming data – for all data workloads. By having all dataaccessible in a single system, organizations can now address all workloads within one unified architecture without trade-offs in performance, scalability, or economics – allowing them to accelerate their journey to real-time insights and seamless AI adoption.
According to Gartner®, “Multiprotocol storage platforms. These are designed to support multiple storage access protocols and address the growing needs of businesses. These platforms are versatile, allowing data to be stored and accessed using different protocols, such as Network File System (NFS), Server Message Block (SMB), block and object. This flexibility enables seamless integration with diverse IT environments and ensures that the storage system can meet the varied requirements of applications and users with different protocol preferences or compatibility needs.”[1]
By incorporating Block storage, VAST has transformed data management for large-scale enterprises, consolidating siloed infrastructure into one platform with a full suite of enterprise data services such as snapshots, multi-tenancy, quality of service (QoS), encryption, and granular Role-Based Access Control (RBAC).
These new features allow VAST to meet the demands of modern enterprise IT infrastructure:
- Seamless Integration with Virtualization Platforms: The VAST Data Platform now provides robust support for environments such as VMware, Hyper-V, and other hypervisors. Features such as multi-tenancy and QoS allow IT teams to isolate workloads, guarantee performance, and simplify resource management across hundreds or thousands of virtual machines.
- Optimized for Kubernetes and Containerized Applications: For organizations leveraging Kubernetes, Openshift or other container orchestration platforms, the addition of Block storage enables persistent storage for containerized workloads. From transactional databases in containers to stateful microservices, the platform delivers the scalability and performance required for DevOps workflows, test environments, and production-grade applications.
- Unified Infrastructure for Hybrid Workloads: In modern enterprise environments, virtualized and containerized workloads often coexist, creating challenges in managing disparate storage systems. The VAST Data Platform eliminates this complexity by consolidating both workload types onto a single, unified storage architecture. This approach reduces operational overhead, simplifies provisioning, and ensures optimal performance across diverse application environments.
- Boot from SAN for Simplified Management and High Availability: With support for Boot from SAN, enterprises can streamline server deployment and management by eliminating reliance on local disks. This approach enhances disaster recovery, improves redundancy, and enables rapid provisioning of new virtual or bare-metal servers while ensuring consistent performance across IT environments.
“Our vision for the VAST Data Platform was always to enable organizations to process, analyze, and act on data in real-time, empowering them to scale effortlessly, reduce their infrastructure costs, and innovate faster by unifying AI data infrastructure within a single, powerful platform,” said Aaron Chaisson, Vice President, Product & Solutions Marketing at VAST Data. “With today’s announcement, we’re eliminating the data silos that once hindered AI and analytics initiatives, affording customers faster, more accurate decisions and unlocking data-driven growth.”
Last Updated on 12 hours by News Desk 1
