Latest news with #dataPlatform
Yahoo
28-05-2025
- Business
- Yahoo
RavenDB and QBS Software Announce Strategic Partnership to Expand NoSQL Innovation Across UK and Europe
LONDON, May 28, 2025--(BUSINESS WIRE)--RavenDB, the pioneer of hybrid NoSQL document databases for modern applications, today announced a strategic partnership with QBS Software, a leading software distributor with a robust network of resellers and system integrators across the UK and Europe. This alliance is set to accelerate the adoption of RavenDB's high-performance, developer-first data platform throughout the region. As part of the partnership, QBS will offer RavenDB solutions through its extensive channel ecosystem, enabling more organizations to build responsive, intelligent applications powered by RavenDB's unmatched performance, hybrid deployment model, and frictionless developer experience. "RavenDB empowers the QBS community to build faster, smarter, and more cost-efficient applications," said David Baruc, Chief Revenue Officer at RavenDB. "By combining a flexible document model with built-in full-text search, automatic indexing, and seamless deployment across cloud, on-prem, and edge, we eliminate the need for multiple tools and reduce infrastructure costs and overhead. It's a modern solution built for real-time performance at scale with a strong ease of use." RavenDB is trusted by Fortune 500s, global ISVs, and innovative startups to manage mission-critical data without compromising speed, flexibility, or cost-efficiency. The platform's built-in distributed architecture and zero-touch operational overhead allow teams to focus on building applications, not managing infrastructure. For QBS Software, the partnership solidifies their reputation as a forward-looking, full spectrum software distributor with a commitment to innovation and strategic growth. Ikramul Khaled, Group Head of Vendor Alliances at QBS Technology Group: "RavenDB enhances the publisher portfolio for QBS Software by adding a high-performance, flexible and scalable NoSQL database solution. With RavenDB being optimised for speed and low-latency performance, especially in distributed systems and cloud environments, this gives QBS a competitive edge in offering scalable database solutions to our partners." As part of the go-to-market collaboration, RavenDB and QBS will jointly host educational webinars, training programs, and partner enablement sessions aimed at accelerating time-to-value for customers and resellers alike. To learn more about the RavenDB-QBS partnership visit About RavenDBRavenDB is the hybrid NoSQL document database built for modern application development. Used by 12,000 companies across 50 industries, RavenDB helps teams move faster with seamless data management across cloud, on-prem, and edge environments. With full-text search, automatic indexes, and an easy-to-use studio for monitoring and administration, RavenDB is the database developers love and enterprises trust. Learn more at About QBS SoftwareQBS Software (QBS) operates the world's largest enterprise software delivery platform, with a network of over 12,500 SaaS vendors. QBS specialises in long-tail software procurement, delivering niche and emerging software solutions. By simplifying software sourcing, procurement, and delivery, QBS empowers partners to focus on driving business growth. Visit View source version on Contacts Media Contact Ron ShelemayChief Marketing Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Forbes
12-05-2025
- Business
- Forbes
How The Microservices Vs. Monoliths Debate Is Damaging Your Business
Beyond The Architecture Cage Match: How The Microservices Vs. Monoliths Debate Is Damaging Your ... More Business In the red corner, weighing in with independent scalability and distributed complexity: microservices! In the blue corner, the reigning legacy champion, with its infamous deployment challenges: the monolith! For years, architects and technology executives have watched this architectural cage match with bated breath. Technology forums buzzed with trash talk from both sides. Conference speakers built careers championing one approach while demonizing the other. Vendors sold middleware solutions promising to crown you champion — if only you'd pick their preferred fighter. But what if we told you that this entire spectacle was all just a waste of time? The truth? Your organization shouldn't pick a single winner in this so-called battle. You need different solutions tailored to specific contexts. The industry landscape is littered with both cautionary tales and success stories that illustrate architectural tension. Consider how Segment, the customer data platform, famously documented its journey from monolith to microservices and then partially back again. The engineering team initially split Segment's platform into over 100 microservices in pursuit of scalability, only to face what they called 'death by a thousand microservices.' The team eventually consolidated back to a more balanced approach after experiencing mounting operational complexity and debugging challenges that outweighed the benefits. On the flip side, many established enterprises cling to aging monoliths long past their expiration dates. When retail giant Target began its digital transformation, it realized that its monolithic architecture couldn't deliver the agility needed to compete with Amazon. Its pragmatic phased approach to modernization — selectively decomposing components while maintaining core systems — helped Target achieve an impressive digital turnaround without falling into either extreme of the architectural spectrum. The lesson from both scenarios? Architectural decisions driven by trends rather than business context frequently lead organizations astray. Architecture is about weighing trade-offs, not adhering to dogma. As we enter a new era of digital acceleration, the organizations pulling ahead aren't arguing about monoliths versus microservices. They're pragmatically applying architectural patterns where they make sense, modernizing incrementally where they see concrete benefits, and staying focused on delivering business value. So go beyond the battle royale, put down the architectural dogma, and start asking better questions about what your specific context, organization, and business needs demand. The true champion of modern software architecture isn't a particular pattern — it's the pragmatic, business-focused approach that delivers real results in your unique context. Because in the real world, the only architectural approach fighter that truly wins is the one that helps your business succeed. This post was written by Principal Analyst Devin Dickerson and Principal Analyst David Mooter and it originally appeared here.
Forbes
07-05-2025
- Business
- Forbes
Nvidia Dynamo And Storage Next Boost AI Storage, Performance And Lowers Costs
AI Inference getty At the 2025 Nvidia GPU Technology Conference the company announced its AI Data Platform that included significant advances in enterprise digital storage to support corporate AI workloads. However, the company's KV cache in its Dynamo software and future looking efforts to connect storage and memory more directly with GPUs will drive digital storage and memory demand further, improve inference performance and lower AI costs. The AI Data Platform leverages Blackwell GPUs, BlueField DPUs and Spectrum-X networking to deliver 1.6X higher performance than CPU-based storage, reducing power consumption by up to 50% and providing more than three types higher performance per watt and accelerating storage traffic up to 48% compared to traditional Ethernet. This roll out was done in conjunction with A number of digital storage companies as shown in the image from Jensen Huang's GTC keynote below. Jensen Huang announcing the AI Data Platform for Enterprise AI Tom Coughlin In a recent conversation with Kevin Deierling from Nvidia we discussed another topic related to storage announcements at the 2025 GTC, that is the Key Value Cache in Nvidia's Dynamo, see image below of Jensen announcing Dynamo. Jensen Huang announces Dynamo Tom Coughlin Jensen characterized Dynamo as the OS of the AI factory. These key values are binary representations of the state of the AI model at a point in time. This KV cache grows to become very large for large models. But the KV cache allows faster user responses and avoids the need to recalculate model results and thus reduces costs and increases efficiency. Nvidia Dynamo is open-source high-throughput low-latency inference software that is intended to standardize model deployment and enables fast and scalable AI in production. Because creating trained KV values for user requests is compute intensive and keeping them solely on GPU memory is expensive the Dynamo KV Cache Manager enables the offloading of older or less frequently access KV cache blocks to more cost-effective memory and storage such as CPU memory, local storage or networked object or file storage. This enables organizations to cost-effectively store petabytes of KV cache data by distributing KV cache blocks between a hierarchy of GPU accessed storage as shown below, depending upon frequency of use. Such a hierarchy will include memory as well as SSDs and HDDs. Dynamo can manage KV cache across multiple GPU nodes and supports both distributed and disaggregated inference serving with the hierarchical caching creating offloading strategies at multiple levels. GPU memory and storage hierarchy Tom Coughlin There is another effort that Nvidia and several digital storage and memory companies are working on that has been called Storage Next. This is an initiative within the Open Compute Project to create a new storage architecture for GPU computing hear memory for disaggregated data-protected, managed block storage using next generation NVMe over the PCIe generation 6 bus. This is expected to provide lower total cost of ownership, higher IOPS, lower power consumption and less complex infrastructure and reduced impact from tail latencies. Kevin's comment to me was that this will include computational storage for AI. Nvidia plans to talk further about this effort at the 2025 FMS in August. Nvidia's Dynamo enables faster and more efficient AI inference with scalable digital storage and memory hierarchical KV caching. Work in development by the storage industry will allow even tighter integration of digital storage with GPUs.
