PeerGFS vs. HULFT IoT

An All-Inclusive Solution for Efficient File Orchestration and Management Across Edge, Data Center, and Cloud Storage PeerGFS offers a uniquely software-driven approach tailored to tackle the complexities of file management and replication in multi-site and hybrid multi-cloud setups. With over 25 years of industry experience, we focus on file replication for organizations with distributed locations, providing numerous advantages for your operations: Increased Availability: Attain elevated availability through Active-Active data centers, whether they are hosted on-premises or in the cloud. Edge Data Security: Protect your essential data at the Edge with ongoing safeguards to the central Data Center. Boosted Productivity: Facilitate distributed project teams by granting them rapid, local access to essential file resources. In the current landscape, maintaining a real-time data infrastructure is crucial for success. PeerGFS effortlessly meshes with your current storage solutions, accommodating: High-volume data replication across linked data centers. Wide area networks that often experience lower bandwidth and increased latency. You can take comfort in knowing that PeerGFS is built for ease of use, ensuring that both installation and management are straightforward tasks. Moreover, our commitment to customer support means you’ll always have assistance when needed.

HULFT IoT acts as a powerful managed file transfer middleware specifically designed for IoT devices, ensuring data integrity in critical situations such as payment processing, security measures, and real-time monitoring. Although collecting IoT data using protocols like MQTT or HTTPS can be challenging for users, HULFT IoT alleviates this difficulty by only requiring the installation of its software, which allows for rapid data acquisition. Furthermore, with the incorporation of DataSpider Servista, our enterprise application integration (EAI) tool, users can effortlessly connect various applications to the data collected by HULFT IoT without the need for any programming, thanks to an intuitive drag-and-drop setup. A machine tool manufacturer that previously relied on conducting in-person inspections and maintenance found that each of their devices produced operational log data during these visits. By examining this log data, they successfully predicted maintenance requirements. In a bid to improve their operational workflow, the manufacturer aimed to implement remote monitoring of their devices and organize maintenance staff as required. However, they faced a significant hurdle, as each device generated around 10GB of log data each day, which added complexity to their data management process. Recognizing the urgency of their situation, they identified the need for an effective and streamlined solution capable of managing such large volumes of data efficiently while maintaining operational effectiveness.