RaimaDB
RaimaDB is an embedded time series database designed specifically for Edge and IoT devices, capable of operating entirely in-memory. This powerful and lightweight relational database management system (RDBMS) is not only secure but has also been validated by over 20,000 developers globally, with deployments exceeding 25 million instances. It excels in high-performance environments and is tailored for critical applications across various sectors, particularly in edge computing and IoT. Its efficient architecture makes it particularly suitable for systems with limited resources, offering both in-memory and persistent storage capabilities. RaimaDB supports versatile data modeling, accommodating traditional relational approaches alongside direct relationships via network model sets. The database guarantees data integrity with ACID-compliant transactions and employs a variety of advanced indexing techniques, including B+Tree, Hash Table, R-Tree, and AVL-Tree, to enhance data accessibility and reliability. Furthermore, it is designed to handle real-time processing demands, featuring multi-version concurrency control (MVCC) and snapshot isolation, which collectively position it as a dependable choice for applications where both speed and stability are essential. This combination of features makes RaimaDB an invaluable asset for developers looking to optimize performance in their applications.
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Epicor Connected Process Control
Epicor Connected Process Control offers an intuitive software solution designed to create and manage digital work instructions while maintaining strict process control, effectively minimizing the chances of errors in operations. By integrating IoT devices, it captures comprehensive time studies and detailed process data, including images, at the task level, providing unprecedented real-time visibility and quality oversight. The eFlex system is versatile enough to accommodate countless product variations and thousands of components, catering to both component-based and model-based manufacturers alike. Furthermore, work instructions seamlessly connect to the Bill of Materials, guaranteeing that products are assembled correctly every time, even when modifications occur during production. This advanced system intelligently adapts to variations in models and components, ensuring that only the relevant work instructions for the current build at the station are presented, enhancing efficiency and accuracy throughout the manufacturing process. In this way, Epicor empowers manufacturers to maintain high standards of quality control while adapting to the dynamic nature of production demands.
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E-MapReduce
EMR functions as a robust big data platform tailored for enterprise needs, providing essential features for cluster, job, and data management while utilizing a variety of open-source technologies such as Hadoop, Spark, Kafka, Flink, and Storm. Specifically crafted for big data processing within the Alibaba Cloud framework, Alibaba Cloud Elastic MapReduce (EMR) is built upon Alibaba Cloud's ECS instances and incorporates the strengths of Apache Hadoop and Apache Spark. This platform empowers users to take advantage of the extensive components available in the Hadoop and Spark ecosystems, including tools like Apache Hive, Apache Kafka, Flink, Druid, and TensorFlow, facilitating efficient data analysis and processing. Users benefit from the ability to seamlessly manage data stored in different Alibaba Cloud storage services, including Object Storage Service (OSS), Log Service (SLS), and Relational Database Service (RDS). Furthermore, EMR streamlines the process of cluster setup, enabling users to quickly establish clusters without the complexities of hardware and software configuration. The platform's maintenance tasks can be efficiently handled through an intuitive web interface, ensuring accessibility for a diverse range of users, regardless of their technical background. This ease of use encourages a broader adoption of big data processing capabilities across different industries.
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Suger
Suger is the modern operating system for Cloud Go-to-Market (Cloud GTM).
We help software companies easily list, sell, and co-sell across leading cloud marketplaces and partner networks, including AWS, Azure, Google Cloud, Snowflake, and Alibaba.
Suger automates the complex, manual work behind Cloud GTM—like managing private offers, syncing with CRMs, fulfilling entitlements, and executing co-sell motions—so sales, ops, and finance teams can focus on revenue, not process overhead.
With an API-first approach and 24+ native integrations, Suger connects directly to your cloud marketplace accounts, CRM, CPQ, billing systems, accounting tools, data warehouse, SSO, and more—powering your entire marketplace lifecycle.
Over 200 SaaS companies—such as Intel, Notion, Webflow, Clari, and Fivetran—rely on Suger to streamline and grow their marketplace revenue.
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