When database software is integrated into an IoT endpoint device, those queries and decisions can be made right on the device, without transferring every record to a back-end data management system first. Duplicating data in different files can help, but maintaining consistency across multiple files quickly becomes a redundancy nightmare.ĭatabase tables allow incoming information to be divided into multiple related records that are easy to search in a variety of ways, with or without SQL. While some analysis is possible with small files on a device, performance quickly becomes an issue when it becomes necessary to relate records that were stored in different files or at different times. Unexpected failures often occur with IoT devices, and if flat files are used for more than simple logging, data corruption is a real possibility that can cause system breakdown.Īs a method of data management, flat files have an advantage when data is only logged and never analyzed or filtered on a device. Only when enough data is accumulated to understand the full context can the software decide which records are most valuable. In many cases, it isn't possible to proactively filter data before it is written to the file system. However, when specific information needs to be searched and analyzed, flat files are not a viable solution. Yet ARM embedded software developers still use flat files to store information in market-dependent formats that are difficult to efficiently analyze and communicate to other systems.įlat files may be adequate when there is only a small volume of data and no need for local reporting. Data is everything in modern development practices, with many convenient ways to manage, access, and share information. Managing data collected on sensors, gateway devices, and embedded systems is a complex task, especially over a long period of time. IoT endpoint devices are responsible for so much information, IoT software developers need to carefully consider how data will be managed and stored.
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