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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Tractian is the Industrial Copilot for maintenance and reliability, combining hardware and software solutions to monitor asset performance, manage industrial operations, and implement predictive maintenance strategies. Its AI-driven platform empowers businesses to prevent unplanned equipment downtime and boost production output. The company is headquartered in Atlanta, GA, and extends its presence globally with offices in Mexico City and Sao Paulo. Learn more at tractian.com.
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SAS Analytics for IoT
Utilize a comprehensive, AI-integrated solution to access, organize, select, and transform data from the Internet of Things. SAS Analytics for IoT encompasses the entire analytics life cycle related to IoT, featuring a streamlined and extensible ETL process, a data model focused on sensors, and an advanced analytics framework supported by a premier streaming execution engine that facilitates complex multi-phase analytics. Powered by SAS® Viya®, this solution operates efficiently within a fast, in-memory distributed setting. Discover how to create SAS Event Stream Processing applications capable of handling high-volume and high-velocity data streams, delivering real-time responses while retaining only the essential data elements. This course introduces fundamental principles of event stream processing, detailing the various component objects that can be utilized to construct effective event stream processing applications. Our commitment to curiosity drives innovation, as SAS analytics solutions convert raw data into actionable insights, empowering customers globally to embark on bold new ventures that foster advancement. Embrace the future of data analytics and unlock limitless possibilities with SAS.
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Lumada IIoT
Implement sensors tailored for IoT applications and enhance the data collected by integrating it with environmental and control system information. This integration should occur in real-time with enterprise data, facilitating the deployment of predictive algorithms to uncover fresh insights and leverage your data for impactful purposes. Utilize advanced analytics to foresee maintenance issues, gain insights into asset usage, minimize defects, and fine-tune processes. Capitalize on the capabilities of connected devices to provide remote monitoring and diagnostic solutions. Furthermore, use IoT analytics to anticipate safety risks and ensure compliance with regulations, thereby decreasing workplace accidents. Lumada Data Integration allows for the swift creation and expansion of data pipelines, merging information from various sources, including data lakes, warehouses, and devices, while effectively managing data flows across diverse environments. By fostering ecosystems with clients and business associates in multiple sectors, we can hasten digital transformation, ultimately generating new value for society in the process. This collaborative approach not only enhances innovation but also leads to sustainable growth in an increasingly interconnected world.
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