This week’s real-time analytics news is dominated by announcements from the NVIDIA GTC conference and KubeCon + CloudNativeCon.
Keeping pace with news and developments in the real-time analytics and AI market can be a daunting task. Fortunately, we have you covered with a summary of the items our staff comes across each week. And if you prefer it in your inbox, sign up here!
NVIDIA used its annual GTC conference to announce the NVIDIA Blackwell platform, which enables organizations to build and run real-time generative AI on trillion-parameter large language models at up to 25x less cost and energy consumption than its predecessor. The Blackwell GPU architecture features six transformative technologies for accelerated computing. Blackwell’s six revolutionary technologies include:
- World’s Most Powerful Chip — Packed with 208 billion transistors, Blackwell-architecture GPUs are manufactured using a custom-built 4NP TSMC process with two-reticle limit GPU dies connected by 10 TB/second chip-to-chip link into a single, unified GPU.
- Second-Generation Transformer Engine — Fueled by new micro-tensor scaling support and NVIDIA’s advanced dynamic range management algorithms integrated into NVIDIA TensorRT-LLM and NeMo Megatron frameworks, Blackwell will support double the compute and model sizes with new 4-bit floating point AI inference capabilities.
- Fifth-Generation NVLink — To accelerate performance for multitrillion-parameter and mixture-of-experts AI models, the latest iteration of NVIDIA NVLink delivers groundbreaking 1.8TB/s bidirectional throughput per GPU, ensuring seamless high-speed communication among up to 576 GPUs for the most complex LLMs.
- RAS Engine — Blackwell-powered GPUs include a dedicated engine for reliability, availability, and serviceability. Additionally, the Blackwell architecture adds capabilities at the chip level to utilize AI-based preventative maintenance to run diagnostics and forecast reliability issues.
- Secure AI — Advanced confidential computing capabilities protect AI models and customer data without compromising performance, with support for new native interface encryption protocols, which are critical for privacy-sensitive industries like healthcare and financial services.
- Decompression Engine — A dedicated decompression engine that supports the latest formats, accelerating database queries to deliver the highest performance in data analytics and data science. In the coming years, data processing, on which companies spend tens of billions of dollars annually, will be increasingly GPU-accelerated.
The Blackwell product portfolio is supported by NVIDIA AI Enterprise, the end-to-end operating system for production-grade AI. NVIDIA AI Enterprise includes NVIDIA NIM inference microservices — also announced at the conference — as well as AI frameworks, libraries, and tools that enterprises can deploy on NVIDIA-accelerated clouds, data centers, and workstations.
The company also announced its Earth-2 climate digital twin cloud platform for simulating and visualizing weather and climate at unprecedented scale. Earth-2’s new cloud APIs on NVIDIA DGX Cloud allow virtually any user to create AI-powered emulations to speed the delivery of interactive, high-resolution simulations ranging from the global atmosphere and local cloud cover to typhoons and turbulence.
In addition to these announcements by the company, many partners also used the conference to break news. Some of these top news items include:
Amazon Web Services (AWS) made multiple announcements at the conference. They include:
- The company will offer new NVIDIA Grace Blackwell GPU-based Amazon EC2 instances and NVIDIA DGX Cloud
- An integration of AWS Nitro System, Elastic Fabric Adapter encryption, and AWS Key Management Service with Blackwell encryption
- Project Ceiba—an AI supercomputer built exclusively on AWS with DGX Cloud—to feature 20,736 GB200 Superchips capable of processing 414 exaflops for NVIDIA’s own AI R&D
- Amazon SageMaker integration with NVIDIA NIM inference microservices helps customers further optimize price performance of foundation models running on GPUs.
Alice & Bob and NVIDIA announced a partnership to integrate quantum computing into the next generation of data centers. Specifically, Alice & Bob integrates NVIDIA DGX Quantum, which combines NVIDIA GH200 Grace Hopper Superchips and the Quantum Machines’ OPX+ control system. The integration will help bring cat qubit-based quantum computers into the ecosystem. Alice & Bob is also using NVIDIA CUDA Quantum, an open-source platform for integrating and programming quantum processing units (QPUs), GPUs, and CPUs in one system, to enable real-time decoding of complex error correction codes, such as qLDPC.
Anyscale announced a collaboration with NVIDIA to integrate the NVIDIA AI Enterprise software platform into the Anyscale platform, enabling customers to accelerate and scale large language models (LLMs) into a production environment with security, support, and stability. The integration brings support for NVIDIA NIM inference microservices announced this week.
Applied Digital Corporation announced today that it will be among the pioneering cloud service providers to use the latest NVIDIA Blackwell platform-based GPUs. Applied Digital plans to integrate NVIDIA’s GPUs into its cloud offerings. This move will provide customers with computing power for intensive tasks such as AI, machine learning, and graphics rendering.
ClearML announced the release of open-source fractional GPU functionality, enabling users to optimize their GPU utilization for free. With this new functionality, DevOps professionals and AI Infrastructure leaders can take advantage of NVIDIA’s time-slicing technology to safely partition their GTX, RTX, and datacenter-grade, MIG-enabled GPUs into smaller fractional GPUs to support multiple AI and HPC workloads without the risk of failure. This allows organizations to optimize usage of their current compute and legacy infrastructure to meet the demands of growing Generative AI use.
Cloudera announced an expanded collaboration with NVIDIA. Cloudera Powered by NVIDIA will integrate enterprise-grade NVIDIA NIM microservices, part of the NVIDIA AI Enterprise software platform, into Cloudera Machine Learning, a Cloudera Data Platform service for AI/ML workflows, to deliver fast, secure, and simplified end-to-end generative AI workflows in production.
Cohesity announced a collaboration with NVIDIA to help organizations safely unlock the power of generative AI and data using the NVIDIA NIM microservices and by integrating NVIDIA AI Enterprise into the Cohesity Gaia platform. The integration of Cohesity Gaia with NVIDIA AI Enterprise will benefit customers by providing direct access to the latest AI capabilities to drive more efficient operations, offering greater insight into security risks and creating more value from their data. T
Databricks announced an expanded collaboration and commitment to deeper technical integrations with NVIDIA. Together, Databricks and NVIDIA will optimize data and AI workloads on the Databricks Data Intelligence Platform. The collaboration builds on NVIDIA’s recent participation in Databricks’ Series I funding round.
Dataloop AI announced that it will collaborate with NVIDIA to integrate the NVIDIA AI Enterprise software platform into its platform to advance the building and refinement of AI applications for businesses. By integrating numerous NVIDIA AI Enterprise software tools and models – including NVIDIA NIM microservices and NVIDIA NeMo Retriever microservices – in its platform, Dataloop offers its customers the ability to speed up AI deployment and enhances their interactions with other tools and applications available on the platform.
DataRobot announced a new collaboration with NVIDIA to accelerate AI use cases. Specifically, its enterprise-ready AI solutions will be supercharged with NVIDIA technology. Through the collaboration, customers can now deploy fully configured generative AI models with NVIDIA NIM microservices, monitor and moderate LLMs with DataRobot custom metrics and NVIDIA NeMo Guardrails, and use NVIDIA RAPIDS libraries within DataRobot Notebooks.
DataStax announced it is supporting enterprise retrieval-augmented generation (RAG) use cases by integrating the new NVIDIA NIM inference microservices and NeMo Retriever microservices with Astra DB to deliver high-performance RAG data solutions for superior customer experiences.
Google Cloud announced a deepened partnership with NVIDIA to provide the machine learning (ML) community with technology that accelerates their efforts when building and scaling generative AI applications. Google announced its adoption of the new NVIDIA Grace Blackwell AI computing platform, as well as the NVIDIA DGX Cloud service on Google Cloud. Additionally, the NVIDIA H100-powered DGX Cloud platform is now generally available on Google Cloud.
Hewlett Packard Enterprise announced updates to its AI-native portfolios to advance the operationalization of generative AI (GenAI), deep learning, and machine learning (ML) applications. The updates include the availability of two HPE and NVIDIA co-engineered full-stack GenAI solutions, a preview of HPE Machine Learning Inference Software, an enterprise retrieval-augmented generation (RAG) reference architecture, and support to develop future products based on the new NVIDIA Blackwell platform.
Hitachi Vantara announced a collaboration with NVIDIA to create a new generation of transformational artificial intelligence (AI) solutions. To that end, Hitachi Vantara will develop a portfolio of solutions, Hitachi iQ, to drive targeted AI outcomes by layering industry-specific capabilities on top of its AI solution stack.
Kinetica unveiled a real-time vector similarity search engine. Under the hood, Kinetica uses NVIDIA RAPIDS RAFT to harness the power of the GPU for vector similarity search. With Kinetica’s combined data and query latency for vector embedding pipelines, large language models (LLM) can immediately augment their results with new information via embeddings as soon as they are generated without delays at scale. The company also announced a generative AI solution that showcases the next step in the evolution of retrieval-augmented generation (RAG).
Lenovo announced new hybrid AI solutions, built in collaboration with NVIDIA, that deliver the power of tailored generative AI applications to users of all types. The hybrid solutions are purpose-built through engineering collaboration to efficiently bring AI to customer data, where and when users need it the most – from the pocket to the cloud. Lenovo hybrid solutions, already optimized to run NVIDIA AI Enterprise software, will now also provide developers access to the just–announced NVIDIA microservices, including NVIDIA NIM and NeMo Retriever.
Microsoft expanded its partnership and longstanding collaboration with NVIDIA with the announcement of powerful new integrations that leverage the latest NVIDIA generative AI and Omniverse technologies across Microsoft Azure, Azure AI services, Microsoft Fabric, and Microsoft 365.
Oracle and NVIDIA announced an expanded collaboration to deliver sovereign AI solutions to customers around the world. Oracle’s distributed cloud, AI infrastructure, and generative AI services, combined with NVIDIA’s accelerated computing and generative AI software, are enabling governments and enterprises to deploy AI factories. These AI factories can run cloud services locally, and within an organization’s secure premises, with a range of operational controls.
Run:ai announced its NVIDIA DGX SuperPOD certification, helping enable scalable and accessible AI computing. This certification underscores Run:ai’s commitment to accelerating AI and machine learning at scale and democratizing AI technologies for wider accessibility within the enterprise.
Schneider Electric announced a collaboration with NVIDIA to optimize data center infrastructure and enable advancements in edge artificial intelligence (AI) and digital twin technologies. Schneider Electric will leverage its expertise in data center infrastructure and NVIDIA’s advanced AI technologies to introduce the first publicly available AI data center reference designs. These designs are set to redefine the benchmarks for AI deployment and operation within data center ecosystems, marking a significant milestone in the industry’s evolution.
Snowflake announced an expanded collaboration with NVIDIA that further empowers enterprise customers with an AI platform, bringing together the full-stack NVIDIA accelerated platform with the trusted data foundation and secure AI of Snowflake’s Data Cloud. In addition to the NVIDIA news, Snowflake announced that it is furthering its partnership with Reka to support its suite of multimodal models in Snowflake Cortex.
Starburst and Dell have teamed to launch a data lakehouse, empowering seamless enterprise data querying with zero movement needed. The collaboration to build the Dell Data Lakehouse has critical components to modernize an organization’s data analytics. Compute is optimized for AI with PowerEdge, featuring the Data Lakehouse System Software based on Kubernetes. The analytics engine, powered by Starburst, allows customers to query all their data together without the need to move it.
UneeQ announced it is now deploying NVIDIA Audio2Face, part of NVIDIA Avatar Cloud Engine (ACE), a suite of technologies that enables real-time digital humans to be even more lifelike. Specifically, NVIDIA ACE seamlessly integrates with UneeQ’s proprietary AI animation system, Synanim, to overcome some of the challenges of delivering lifelike digital animations in real time. The enhancement, which speeds up response time, has proven to deliver higher conversions, improved customer service and customer journeys, better staff training, and enhanced web and immersive experiences.
Vertiv announced it is joining the NVIDIA Partner Network (NPN) as a Solution Advisor: Consultant, bringing Vertiv’s high-density power and cooling infrastructure expertise to better support the adoption of accelerated computing and AI workloads. Additionally, Cadence Design Systems announced its collaboration with Vertiv and NVIDIA for the Cadence Reality Digital Twin Platform to assist in data center design for the AI era.
Voltron Data announced that it has significantly advanced spilling out of GPU memory performantly in Theseus, an accelerator-native distributed query engine built to leverage the latest hardware and software innovations to solve data challenges too big and time-sensitive for Spark. With this new release, Theseus has achieved a new level of performance and scale, completing the full TPC-H 100 terabyte-scale factor on unsorted Parquet files directly from storage in less than an hour with only five terabytes of GPU memory.
Vultr announced the launch of Vultr Cloud Inference. Vultr Cloud Inference provides customers with seamless scalability, reduced latency, and enhanced cost efficiency for their AI deployments. With the solution, users can bring their own model, trained on any platform, cloud, or on-premises, and it can be seamlessly integrated and deployed on Vultr’s global NVIDIA GPU-powered infrastructure. The company also announced a strategic partnership with Singtel to expand its capacity of NVIDIA GPUs in Singapore and across Southeast Asia.
WekaIO (WEKA) unveiled WEKApod, a new data platform appliance certified for NVIDIA DGX SuperPOD with NVIDIA DGX H100 systems. WEKApod delivers all the capabilities of WEKA’s Data Platform software in an easy-to-deploy appliance for enterprise AI, generative AI, and GPU cloud customers. The appliance integrates WEKA’s AI-native data platform software with class-leading storage hardware to provide a ready-to-use, purpose-built environment for AI applications.
Wind River demonstrated the use of Wind River Linux with the NVIDIA Jetson platform for advanced generative AI at-the-edge applications. In the demonstration, the combination of the Yocto Project–based Wind River Linux and NVIDIA Jetson Orin provided a CUDA-optimized solution for real-time object recognition in dashcam videos.
Real-time analytics news in brief
Amazon Web Services (AWS), Accenture, and Anthropic announced that they are coming together to help organizations—especially those in highly regulated industries, including healthcare, public sector, banking, and insurance—responsibly adopt and scale customized generative artificial intelligence (AI) technology within their organizations. Through this collaboration, organizations can access Anthropic’s AI models through Amazon Bedrock, a fully managed service that offers a choice of high-performing foundation models from leading AI companies and Amazon via a single application programming interface. In addition, organizations will gain access to a broad set of capabilities they need to build generative AI applications with security, privacy, and responsible AI.
Apica announced that it has partnered with Boomi to deliver Run-Time Observability (RTO) powered by the Apica Ascent platform. RTO will provide Boomi customers with comprehensive monitoring and alerting of the Boomi runtime and the underlying infrastructure to ensure customer-managed runtimes remain healthy and operational. This will provide Boomi customers with visibility into the performance of Boomi workloads and APIs, giving Boomi customers enhanced levels of control over their integration and automation pipelines.
Confluent announced new Confluent Cloud features that provide enhanced reliability and security, making it easier for customers to work with Apache Iceberg and enrich their data streams. One element of the announcement is that Confluent Cloud for Apache Flink is now generally available across all three major cloud service providers. Additionally, Confluent released TableFlow, a new feature within the Kora Engine that allows customers to convert Kafka topics, schemas, and metadata to Apache Iceberg tables in one click.
The Fluent Bit community announced the release of Fluent Bit v3, which includes several new features, quality of life improvements, and performance enhancements for the popular open-source telemetry agent. New features in Fluent Bit v3 include integration with a variety of emerging open standards, making the already-ubiquitous project even more relevant to evolving, modern workloads in the cloud and at the edge.
HEAVY.AI announced HeavyIQ. HeavyIQ brings Large Language Model (LLM) capabilities to the GPU-accelerated HEAVY.AI analytics platform, enabling organizations to interact with their data through conversational analytics. The technology employs the power of an LLM in conjunction with retrieval augmented generation (RAG) capabilities to take a user’s text input, automatically convert it into a SQL query, and can both visualize and return natural language summaries of results. With HeavyIQ, HEAVY.AI has taken an open-source LLM foundation model and extensively trained it to excel at core analytics tasks, including analyzing massive geospatial and temporal data sets.
HiveMQ announced the general availability of HiveMQ Edge, a software-based industrial edge MQTT gateway designed to bridge the Operational Technology (OT) and Information Technology (IT) divide for smart manufacturing, automotive, transportation and logistics, and energy use cases. HiveMQ Edge is optimized to help companies get data out of edge systems, improve data quality and integrity with HiveMQ Data Hub, build a Unified Namespace by enabling seamless data integration to a centralized data hub, and achieve enterprise-grade reliability with support for offline buffering.
Kong announced the release of Kong Gateway Operator (KGO) 1.2. This is the first open-source release of KGO. This latest version allows users to deploy and manage the Kong Gateway in a Kubernetes-native manner, offering flexibility for Kubernetes platform teams. When using vendor-neutral Gateway API resources, KGO will automatically deploy the Kong Ingress Controller and Kong Gateway Data Planes, either separately or together, when running on Kubernetes.
Kubecost announced the launch of Kubecost 2.2. Among the new capabilities included in Kubecost 2.2 are carbon cost monitoring and disk autoscaler, which automates disk scaling based on EBS persistent volume utilization. The new release also features Datadog cost monitoring. By directly integrating Datadog cost data, the Kubecost 2.2 release offers granular and real-time visibility into usage and costs, enabling developers, FinOps, and platform engineering teams to optimize resources and bring down costs.
Matillion announced a platform to unify pushdown ELT and pushdown AI to allow data engineers to build Analytics & AI pipelines faster on top of platforms like Snowflake, Databricks, and AWS. Bringing a set of integrated Generative AI capabilities to general availability, Matillion’s unified pushdown ELT and pushdown AI cloud data integration platform enables data teams to become more productive with AI assistance, unlock new unstructured data sources, and build new AI pipelines for new business applications such as chat bots.
ngrok announced support for the Kubernetes Gateway API, now available in developer preview through its ngrok Kubernetes Operator. To use the KubernetesGateway API, cluster operators can set up a Gateway on their cluster, which can have multiple listeners. These listeners will be connected to ngrok endpoints and edges. Application developers will have the ability to create routes that can alter traffic and direct it towards backends, such as Kubernetes Services.
OutSystems announced updates to OutSystems Developer Cloud. With the launch of OutSystems Data Fabric, organizations can lay the groundwork to build dynamic applications, harness data across the enterprise, and increase developer productivity. This latest addition to the OutSystems Developer Cloud serves as an integrated virtual data layer that’s usable across the IT ecosystem.
Redpanda announced the availability of Redpanda Serverless, a fully managed, pay-as-you-go edition of its powerful streaming data platform. Redpanda Serverless empowers developers to get started with streaming data in seconds and to automatically scale the service up or down to match their data workloads. As with all Redpanda products, Redpanda Serverless is fully Apache Kafka API-compatible, ensuring it works with the complete Kafka ecosystem without requiring changes to application code.
Sentry announced the release of Autofix, an AI-powered feature to debug and fix code in minutes, saving important time and resources. The feature understands what users are doing when an error occurs, analyzes the error, generates a fix, and opens a pull request for review. Autofix uses an agent-based architecture to break the process of evaluating and fixing into manageable units of work. The system will also proactively ask for context and feedback as it proceeds, and the result of each step is presented in a CI-like interface that should feel familiar to developers.
Stardog announced the general release of Stardog Voicebox, its Large Language Model Platform (LLM). Additionally, Stardog launched Stardog Karaoke, an appliance version of Voicebox that will enable highly-regulated businesses that utilize a hybrid cloud strategy to reap the enormous benefits of Voicebox and Generative AI (GenAI).
SUSE announced enhancements across its cloud-native and Edge portfolio to enable customers to securely deploy and manage business-critical workloads anywhere. New capabilities in Rancher Prime 3.0, SUSE’s commercial offering of Rancher, the widely adopted open-source enterprise container management platform. New capabilities in Rancher Prime 3.0 help platform engineering teams deliver self-service Platform-as-a-Service (PaaS) to their developer communities and enhanced support for AI workloads. It also announced SUSE Edge 3.0, which extends the power of open source to the edge.
Traefik Labs announced product updates that address the escalating adoption of Kubernetes and the crucial role of API management in modern digital infrastructure. The updates include a Kubernetes-native API gateway, integration of a Web Application Firewall (WAF), and advanced API management capabilities that improve governance and security. The Traefik Hub API Gateway is engineered to provide a native Kubernetes experience while providing ease of use, along with streamlined integration with existing infrastructure and a simplified transition for those scaling from Traefik Proxy open-source (3.2 billion downloads) to a fully-featured, production-grade API gateway product.
UiPath announced several new generative AI (GenAI) features in its platform designed to help enterprises realize the full potential of AI with automation by accessing powerful, specialized AI models. The new features include new LLMs, DocPATH, and CommPATH; context grounding to augment GenAI models with business-specific data; GenAI connectors; and an IBM watsonx.ai connector. The new connector provides UiPath customers with access to multiple foundational models currently available in watsonx.ai. Additional new features include UiPath Autopilot for developers and testers and prebuilt GenAI Activities that use the UiPath AI Trust Layer for faster time to value.
If your company has real-time analytics news, send your announcements to [email protected].
In case you missed it, here are our most recent previous weekly real-time analytics news roundups:
- Real-time Analytics News for the Week Ending March 16
- Real-time Analytics News for the Week Ending March 9
- Real-time Analytics News for the Week Ending March 2
- Real-time Analytics News for the Week Ending February 24
- Real-time Analytics News for the Week Ending February 17
- Real-time Analytics News for the Week Ending February 10
- Real-time Analytics News for the Week Ending February 3
