Skip to content Skip to navigation

ryanp's blog

Leveraging Database Replication for Incremental Backup

Regular backups are a common technique to protect critical data from hardware failure. But for embedded devices that continuously collect and analyze IoT sensor data for months or years at a time, a full backup is often too large to run frequently. Instead, incremental backups ensure that new data is continuously protected. Devices also need to run autonomously, without a system administrator, so any backup solution needs to be easy to automate.

How to Build Edge Devices with a Strong Industrial IoT Data Management Framework

The Internet of Things, IoT, is inviting devices to change our lives. From managing home appliances to vehicles interacting with roads and cities, devices can advise one on what to do, what to eat, where to go and how to get there. When it comes to the industrial aspect of IoT, devices assist in managing processes during which alarm management adds value to predict faults and catastrophes. Things are getting embedded with and controlled by smart devices that come together to automate tasks, so we can maximize our time. Intelligent things can collect, transmit and understand information.

Going Beyond Flat File Data on IoT Devices with Embedded Database

IoT endpoint devices are responsible for so much information, IoT software developers need to carefully consider how data will be managed and stored. Managing data collected on sensors, gateway devices, and embedded systems is a complex task, especially over a long period of time. Data is everything in modern development practices, with many convenient ways to manage, access, and share information. 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.

Database in a new era of application development

A new age is dawning for the development of applications on embedded systems and devices. This era is about connecting billions of devices, each containing a wealth of information. How can you prepare to design and build the connected, data-driven applications of the future?

Developers and manufacturers are seeking new alternatives to improve performance, reduce cost, and keep up with growing data. In this new article, discover the aspects of embedded data management that will be most important for the development of your next product.

Securing embedded applications

Data security is most effective when it is built-in to applications, rather than relying on system-level security measures alone. An application can protect data by storing it in an encrypted database file, which can either be opened directly or accessed through a separate database server process. If data is replicated or accessed remotely, network communications must also be encrypted with a secure protocol that prevents eavesdropping and session hijacking. ITTIA DB SQL provides these important security features in an embedded database library.

Machine to Machine

ITTIA's M2M solution offers embedded system developers an easy way to connect applications and communicate information. For example, a home automation application can monitor the cycle of a washing machine, schedule a coffee machine to finish brewing at a specific time, and check that lights are off when away from home. Residents need to access and control information on these devices through multiple interfaces, whether mounted in the home or on a personal smart phone or tablet. A database for such devices must provide a framework for communication within the M2M infrastructure.

Big Data and Embedded Database for Devices

Applications for embedded systems – including medical devices, industrial automation, automotive software, and mobile tablets – often encounter serious data management challenges in which a large amount of data is collected and accumulated at different locations. Typical queries required by end users of these systems are not easily met.

With ITTIA DB SQL a large data set can be distributed across a wide array of devices, with the potential to store millions of rows per device.

Table cursors

Data management and query analysis are important criteria for interacting with embedded data. ITTIA DB SQL offers embedded developers two independent methodologies for managing and running queries: SQL and direct low-level access. Benefits include performance tuning, speedy query execution, code simplicity, and reduced overhead when detouring around SQL. These rich APIs provide flexibility for embedded developers.

Pages

Subscribe to RSS - ryanp's blog