Pavilion HyperOS Integrations

TensorFlow is a comprehensive open-source machine learning platform that covers the entire process from development to deployment. This platform boasts a rich and adaptable ecosystem featuring various tools, libraries, and community resources, empowering researchers to advance the field of machine learning while allowing developers to create and implement ML-powered applications with ease. With intuitive high-level APIs like Keras and support for eager execution, users can effortlessly build and refine ML models, facilitating quick iterations and simplifying debugging. The flexibility of TensorFlow allows for seamless training and deployment of models across various environments, whether in the cloud, on-premises, within browsers, or directly on devices, regardless of the programming language utilized. Its straightforward and versatile architecture supports the transformation of innovative ideas into practical code, enabling the development of cutting-edge models that can be published swiftly. Overall, TensorFlow provides a powerful framework that encourages experimentation and accelerates the machine learning process.

IBM Cloud® offers features that enhance both business agility and resilience, allowing users to discover a platform that provides 2.5 times the value. Tailored for various industries, it emphasizes security and the flexibility to develop and operate applications in any environment. The platform facilitates the transformation of business workflows through the integration of automation and artificial intelligence. Furthermore, it boasts a robust technology partner ecosystem that addresses specific industry demands, leveraging deep expertise and tailored solutions. Its processes are automated and auditable, ensuring compliance and efficiency. With unique functionalities ensuring top-tier cloud security and monitoring, users benefit from a uniform security and control framework across all applications. Additionally, its containerized solutions foster seamless DevOps practices, automation, data management, and security enhancements. The platform offers streamlined integration along with a consistent application development lifecycle, making it user-friendly. Beyond these features, IBM Cloud harnesses advanced technologies such as IBM Watson®, analytics, the Internet of Things (IoT), and edge computing, enabling businesses to innovate and stay ahead of the competition.

Amazon Simple Storage Service (Amazon S3) serves as an object storage solution renowned for its exceptional scalability, data availability, security, and performance. This versatile service enables businesses of all sizes across various sectors to securely store and safeguard an unlimited volume of data for numerous applications, including data lakes, websites, mobile apps, backup and recovery, archiving, enterprise solutions, Internet of Things (IoT) devices, and big data analytics. With user-friendly management tools, users can efficiently organize their data and establish precise access controls that align with their unique business and compliance needs. Amazon S3 is engineered to ensure an impressive durability rate of 99.999999999% (11 nines), making it a reliable choice for millions of applications utilized by companies globally. Customers can easily adjust their storage capabilities up or down to adapt to changing demands, eliminating the need for initial investments or prolonged resource acquisition processes. Additionally, the service's robust infrastructure supports a diverse range of data management strategies, further enhancing its appeal to organizations seeking reliable and flexible storage solutions.

Transforming data into actionable insights is made simple with Splunk, which is securely and reliably managed as a scalable service. By entrusting your IT backend to our Splunk specialists, you can concentrate on leveraging your data effectively. The infrastructure, provisioned and overseen by Splunk, offers a seamless, cloud-based data analytics solution that can be operational in as little as 48 hours. Regular software upgrades guarantee that you always benefit from the newest features and enhancements. You can quickly harness the potential of your data in just a few days, with minimal prerequisites for translating data into actionable insights. Meeting FedRAMP security standards, Splunk Cloud empowers U.S. federal agencies and their partners to make confident decisions and take decisive actions at mission speeds. Enhance productivity and gain contextual insights with the mobile applications and natural language features offered by Splunk, allowing you to extend the reach of your solutions effortlessly. Whether managing infrastructure or ensuring data compliance, Splunk Cloud is designed to scale effectively, providing you with robust solutions that adapt to your needs. Ultimately, this level of agility and efficiency can significantly enhance your organization's operational capabilities.

Apache Kafka® is a robust, open-source platform designed for distributed streaming. It allows for the scaling of production clusters to accommodate up to a thousand brokers, handling trillions of messages daily and managing petabytes of data across hundreds of thousands of partitions. The system provides the flexibility to seamlessly expand or reduce storage and processing capabilities. It can efficiently stretch clusters over various availability zones or link distinct clusters across different geographical regions. Users can process streams of events through a variety of operations such as joins, aggregations, filters, and transformations, with support for event-time and exactly-once processing guarantees. Kafka features a Connect interface that readily integrates with numerous event sources and sinks, including technologies like Postgres, JMS, Elasticsearch, and AWS S3, among many others. Additionally, it supports reading, writing, and processing event streams using a wide range of programming languages, making it accessible for diverse development needs. This versatility and scalability ensure that Kafka remains a leading choice for organizations looking to harness real-time data streams effectively.

Flywheel provides comprehensive data management solutions to researchers looking to improve productivity and collaboration in imaging research and clinical trials, multi-center studies, and machine learning. Flywheel provides end-to-end solutions that streamline data ingestion and curate it to common standards. We also automate processing and machine-learning pipelines. Our platform allows for secure collaboration in the life sciences, clinical, academic, as well as AI, industries. Cross-platform data and algorithm integration, secure and compliant data discovery among a global network, and cloud-scalable and on-premise computational workflows to support research and clinical applications. Flywheel is a data curation platform that supports multi-modality research. It can manage a wide range of data types, including digital pathology, imaging files, clinical EMR data and omics, as well as instruments.

Greenplum Database® stands out as a sophisticated, comprehensive, and open-source data warehouse solution. It excels in providing swift and robust analytics on data volumes that reach petabyte scales. Designed specifically for big data analytics, Greenplum Database is driven by a highly advanced cost-based query optimizer that ensures exceptional performance for analytical queries on extensive data sets. This project operates under the Apache 2 license, and we extend our gratitude to all current contributors while inviting new ones to join our efforts. In the Greenplum Database community, every contribution is valued, regardless of its size, and we actively encourage diverse forms of involvement. This platform serves as an open-source, massively parallel data environment tailored for analytics, machine learning, and artificial intelligence applications. Users can swiftly develop and implement models aimed at tackling complex challenges in fields such as cybersecurity, predictive maintenance, risk management, and fraud detection, among others. Dive into the experience of a fully integrated, feature-rich open-source analytics platform that empowers innovation.

Teradata presents VantageCloud, an all-encompassing cloud analytics solution aimed at speeding up innovation powered by data. By combining artificial intelligence, machine learning, and immediate data processing capabilities, VantageCloud empowers organizations to convert unrefined data into useful insights. The platform caters to various applications, such as sophisticated analytics, business intelligence, and transitioning to the cloud, while offering effortless deployment in public, hybrid, or on-site setups. With Teradata's powerful analytics capabilities, businesses can harness the full potential of their data, enhancing operational efficiency and discovering fresh avenues for growth in multiple sectors. This adaptability makes VantageCloud a vital asset for organizations looking to thrive in a data-driven landscape.

Dell EMC Avamar facilitates quick and efficient data backup and recovery by utilizing its advanced variable-length deduplication technology. It is specifically designed to perform rapid, daily full backups across a range of environments, including physical and virtual systems, NAS servers, enterprise applications, as well as remote offices and personal devices. Available in both virtual edition and as part of the comprehensive Dell EMC Data Protection Suite, Avamar provides a wide array of data protection software options. It is particularly effective for virtual environments and ensures application-consistent recovery for critical enterprise applications. By employing variable-length deduplication, it achieves impressive performance while minimizing costs. Additionally, it offers a user-friendly centralized management interface and robust encryption features to enhance data security. Moreover, Dell Technologies On Demand presents an extensive array of consumption-based and as-a-service solutions that align perfectly with the evolving needs of on-premises infrastructure and services in today’s on-demand economy. This flexibility ensures that businesses can scale their resources efficiently while maintaining control over their data management strategies.

The Apache Hadoop software library serves as a framework for the distributed processing of extensive data sets across computer clusters, utilizing straightforward programming models. It is built to scale from individual servers to thousands of machines, each providing local computation and storage capabilities. Instead of depending on hardware for high availability, the library is engineered to identify and manage failures within the application layer, ensuring that a highly available service can run on a cluster of machines that may be susceptible to disruptions. Numerous companies and organizations leverage Hadoop for both research initiatives and production environments. Users are invited to join the Hadoop PoweredBy wiki page to showcase their usage. The latest version, Apache Hadoop 3.3.4, introduces several notable improvements compared to the earlier major release, hadoop-3.2, enhancing its overall performance and functionality. This continuous evolution of Hadoop reflects the growing need for efficient data processing solutions in today's data-driven landscape.

Create, execute, oversee, link, and safeguard all your applications across any cloud environment. VMware's Multi-Cloud solutions provide a cloud operating framework suitable for all types of applications. Propel your digital transformation efforts with the most reliable and widely adopted cloud infrastructure available today. Utilize the same expertise you apply in your data center while accessing a vast network of six major hyperscale public cloud providers and over 4,000 VMware Cloud Provider Partners. By employing a hybrid cloud approach through VMware Cloud Foundation, you can achieve uniform infrastructure and operations for both new and existing cloud-native applications, spanning from the data center to the cloud and extending to the edge. This uniformity fosters enhanced agility while minimizing complexity, expenses, and risks. You can develop, run, and manage contemporary applications across any cloud, addressing various demands with resources from both on-premises and public cloud environments. Furthermore, you have the capability to manage both containerized workloads and traditional VM-based workloads seamlessly on one cohesive platform, ensuring efficiency and adaptability.

StarWind HCA is delivered fully pre-configured and tailored to meet your specific needs by experienced StarWind Engineers. The company facilitates seamless migration to its platform at no additional expense, ensuring there are no concealed fees or licensing issues, as StarWind HCA features standardized and transparent licensing. This approach is a distinctive offering from StarWind that is not available for free from other HCI providers. Furthermore, every StarWind HCA license comes with the StarWind Command Center, a comprehensive web interface for management and monitoring, allowing users to oversee their hardware (networking and storage) and software resources (workloads, virtual machines, and backups) from a single, user-friendly HTML5 dashboard. StarWind carefully selects only top-quality components from the most reputable hardware manufacturers, eliminating the need for a traditional, cluttered data center setup. Everything essential is integrated into this compact HCI platform, making it a truly hassle-free solution that streamlines operations while maximizing efficiency. With this innovative approach, users can focus on their core tasks without being bogged down by technical complexities.

GlusterFS is an adaptable network filesystem designed for high-demand applications, including cloud storage solutions and media streaming. This software is both free and open source, making it compatible with readily available hardware. It functions as a scalable, distributed file system that merges storage resources from various servers into a unified global namespace. Organizations have the flexibility to expand their capacity, performance, and availability as needed without being tied to a specific vendor, whether they operate on-premises, in the public cloud, or in hybrid settings. Many organizations across diverse sectors such as media, healthcare, government, education, web 2.0, and financial services have adopted GlusterFS for their production environments. The system is capable of scaling to several petabytes and efficiently managing thousands of clients while ensuring POSIX compatibility. It operates on standard commodity hardware and supports any on-disk filesystem that allows extended attributes. Furthermore, GlusterFS can be accessed via widely-used protocols like NFS and SMB, and it offers essential features including replication, quotas, geo-replication, snapshots, bitrot detection, and much more, ensuring data integrity and availability. Its versatility and robust capabilities make it a preferred choice for organizations looking to optimize their data storage solutions.

Apache Spark™ serves as a comprehensive analytics engine designed for extensive data processing tasks. It delivers exceptional performance for both batch and streaming workloads, utilizing an advanced Directed Acyclic Graph (DAG) scheduler, a sophisticated query optimizer, and an efficient physical execution engine. With over 80 high-level operators available, Spark simplifies the development of parallel applications. Additionally, users can interact with it through various shells, such as Scala, Python, R, and SQL. Spark supports a robust ecosystem of libraries, including SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Spark Streaming for real-time data processing, allowing for seamless integration of these libraries within a single application. The platform is versatile, capable of running on multiple environments like Hadoop, Apache Mesos, Kubernetes, standalone setups, or cloud services. Furthermore, it can connect to a wide array of data sources, enabling access to information stored in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other systems, thus providing flexibility to meet various data processing needs. This extensive functionality makes Spark an essential tool for data engineers and analysts alike.