RaimaDB
RaimaDB, an embedded time series database that can be used for Edge and IoT devices, can run in-memory. It is a lightweight, secure, and extremely powerful RDBMS. It has been field tested by more than 20 000 developers around the world and has been deployed in excess of 25 000 000 times.
RaimaDB is a high-performance, cross-platform embedded database optimized for mission-critical applications in industries such as IoT and edge computing. Its lightweight design makes it ideal for resource-constrained environments, supporting both in-memory and persistent storage options. RaimaDB offers flexible data modeling, including traditional relational models and direct relationships through network model sets. With ACID-compliant transactions and advanced indexing methods like B+Tree, Hash Table, R-Tree, and AVL-Tree, it ensures data reliability and efficiency. Built for real-time processing, it incorporates multi-version concurrency control (MVCC) and snapshot isolation, making it a robust solution for applications demanding speed and reliability.
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QuantaStor
QuantaStor, a unified Software Defined Storage platform, is designed to scale up and down to simplify storage management and reduce overall storage costs. QuantaStor storage grids can be configured to support complex workflows that span datacenters and sites. QuantaStor's storage technology includes a built-in Federated Management System that allows QuantaStor servers and clients to be combined to make management and automation easier via CLI and RESTAPIs. QuantaStor's layered architecture gives solution engineers unprecedented flexibility and allows them to design applications that maximize workload performance and fault tolerance for a wide variety of storage workloads. QuantaStor provides end-to-end security coverage that allows multi-layer data protection for cloud and enterprise storage deployments.
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Huawei FusionCube
Huawei's FusionCube hyper-converged infrastructure unifies compute, storage, networking, virtualization, and management into a seamless solution designed for exceptional performance, minimal latency, and swift deployment. The integrated distributed storage engines within FusionCube facilitate a profound convergence of computing and storage capabilities. These proprietary engines from Huawei effectively eliminate performance bottlenecks, providing users with the ability to expand capacity flexibly. FusionCube is compatible with leading industry databases and virtualization platforms. Additionally, the Huawei FusionCube 1000 HyperVisor&Data functions as a data storage infrastructure built on a converged architecture. It comes pre-integrated with a distributed storage engine, virtualization software, and cloud management tools, enabling on-demand resource allocation and straightforward linear expansion. This comprehensive approach ensures that organizations can scale their resources efficiently as their needs evolve.
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IBM VersaStack
The VersaStack solution, a collaborative effort between IBM and Cisco, integrates a wide array of converged infrastructure and software-defined technologies aimed at accelerating digital transformation. This innovative platform enhances the simplicity, efficiency, and adaptability of deployments in cloud computing, big data, and enterprise applications. It facilitates autonomous operations within data centers while significantly reducing capital expenditures, operating costs, and total cost of ownership (TCO). Resources can be dynamically allocated from a pool of compute, network, and storage options, whether on-premises or within the cloud. By supporting hybrid environments and IT as a Service (ITaaS), VersaStack enables seamless deployments across on-premises, private, and public cloud infrastructures. With its robust IT automation capabilities, the solution is designed for versatile use in public, private, and hybrid cloud settings. It addresses varying capacity requirements through a range of all-flash and hybrid data storage solutions, optimizes existing storage systems, and accommodates block, file, and object data. This comprehensive approach ensures that organizations can effectively manage and scale their data infrastructure to meet evolving business demands.
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