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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Couchbase’s operational data platform for AI is a scalable foundation for enterprise operational, analytical, mobile and AI workloads that replaces legacy infrastructure and data services. Couchbase connects and mobilizes your data, so you can power peak experiences, harness the power of AI and scale globally—all with less risk and lower overhead.
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Dragonfly serves as a seamless substitute for Redis, offering enhanced performance while reducing costs. It is specifically engineered to harness the capabilities of contemporary cloud infrastructure, catering to the data requirements of today’s applications, thereby liberating developers from the constraints posed by conventional in-memory data solutions. Legacy software cannot fully exploit the advantages of modern cloud technology. With its optimization for cloud environments, Dragonfly achieves an impressive 25 times more throughput and reduces snapshotting latency by 12 times compared to older in-memory data solutions like Redis, making it easier to provide the immediate responses that users demand. The traditional single-threaded architecture of Redis leads to high expenses when scaling workloads. In contrast, Dragonfly is significantly more efficient in both computation and memory usage, potentially reducing infrastructure expenses by up to 80%. Initially, Dragonfly scales vertically, only transitioning to clustering when absolutely necessary at a very high scale, which simplifies the operational framework and enhances system reliability. Consequently, developers can focus more on innovation rather than infrastructure management.
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Lenovo ThinkAgile VX Series
Installing a new hyperconverged infrastructure is often a project that requires significant do-it-yourself effort from customers, who need to handle the configuration, testing, debugging, optimization, and validation on their own. In contrast, the ThinkAgile VX Series simplifies this process by completing those necessary steps before the system even leaves the factory. When it arrives, the VX Series comes equipped with everything you need to get started, along with the support of Lenovo professional services for installation and configuration assistance. For a hyperconverged solution to be effective, it is crucial to have a dependable platform. The ThinkAgile VX Series combines Lenovo's top-tier servers with VMware vSAN, creating a robust base for business growth. It provides the flexibility to be configured for various use cases, and customers can choose from all-flash or hybrid configurations. Furthermore, scaling either compute or storage capacity is straightforward; you can begin with as few as three nodes and easily expand by either increasing the storage in each node or adding additional nodes to enhance performance and capacity. This adaptability makes the VX Series an ideal choice for businesses anticipating growth.
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