Overview
Edge data management for the Industrial Internet of Things (IIoT) creates tremendous opportunities, innovations and cost savings as it brings computation, analysis and data management to the embedded systems close to where the data is actually generated. It enables the refining of data, the gaining of insights and acting on time series data for modern industrial embedded systems. Edge data management also interacts with and prepares data for ingestion into Artificial Intelligence (AI) and Machine Learning (ML) components that will be part of virtually every modern IIoT system.
ITTIA database products enable embedded systems at the edge to manage and process data and offers great benefits such as smoothing, structuring and refining real-time data. Whether you are building embedded systems for chemical refineries, industrial control systems, water purification for municipalities or medical device robots that must collect, process and structure a large volume of time series device data, it is important to learn about ITTIA database product features and exceptional high-performance capabilities.
IIoT Data Management Challenges
When it comes to time series data processing and real-time data management at the edge, many obstacles exist in various industrial markets. While the current systems have seen a significant amount of investment over the years, these systems are coming to the end of their viable lifetimes and are in need of upgrades and/or replacement. Virtually every one of these systems was built for a single purpose or function and are, therefore, very inflexible from an evolution perspective. To position themselves for future changes and/or technologies, industrial companies prefer transforming their existing implementations into a software-defined architecture.
Because so much of the deployed technology and software is reaching the end of its useful life, maintenance expenses are rising considerably. Upkeep on older equipment is getting increasingly expensive. The ability of manufacturers to adopt new technology is constrained by these outdated platforms that were not designed to handle, comprehend, and manage significant amounts of complex data. Data management for connected IIoT systems is a rapidly evolving need, and optimizing industrial systems with secure local data management at the edge where data originates is quickly becoming a new key requirement. As AI and ML functions become readily available at the edge, the need for pre-processing data to optimize the execution of these functions becomes critical.
As manufacturers are building applications for an autonomous tomorrow, machine learning and time series data management and processing will offer foundations to build resilient industrial systems and increase the monetary value by processing and understanding data. All these systems share similar edge data management requirements. Nowadays, more and more devices and embedded systems are starting to be connected, and there is great concern about data security, storage size, communication bandwidth, maintenance cost and ownership.
IIoT and Data Management Solution
IIoT systems require secure time series data monitoring, robust processing and structured storage capabilities. Manufacturers of these systems are transitioning from fixed feature systems with limited functionalities to software-defined embedded systems running on new, sophisticated, powerful microcontrollers and microprocessors.
Industrial systems are transitioning and defining new architectures and devices that are both more intelligent and much more autonomous. Locally managing the data created by these architectures and devices will be critical to their success and longevity.
Processing data on the edge and sharing and storing information is becoming the norm for most modern industrial systems. Due to security, performance and cost of data maintenance and ownership, manufacturers are opting to keep the data computing and maintenance mostly on the edge in the device, using cloud services for long term trending and large data analysis. Locally managing, structuring and refining device data is also a critical enabler to embedded Artificial Intelligence and Machine Learning engines. Being able to ingest time-series data that has been optimized for these platforms will make them much faster, more efficient and more effective in improving device performance.
Benefits of ITTIA DB for Industrial Systems
ITTIA offers database and data management products that meet the needs of virtually all modern industrial embedded edge devices. All of these come with minimal administrative requirements and memory footprint, combined with powerful functionality for IIoT embedded systems and devices. ITTIA DB products empower these industrial systems to structure, perform optimizations and process locally critical data which is then made accessible to software-defined systems embedded with Artificial Intelligence and Machine Learning components. Applications built with ITTIA DB products are safe, secure, reliable, and certifiable.
Industrial systems manufacturers seek to understand data in applications built for smart connected systems. Modern databases like ITTIA DB enable devices to capture and organize data for advanced querying, aggregation, and filtering. It provides quick access to the data that matters and scales to many devices.
To achieve real time data monitoring objectives, innovations with ITTIA DB are poised to make industrial systems fundamentally benefit from edge data management and processing capabilities. ITTIA DB’s added value includes expansion of data access throughout the entire systems, device empowerment for quick real time decision making and time series data analytics. ITTIA DB also offers manufacturers easy, cost-efficient methods to run data campaigns across their systems for preventive maintenance, system behavior monitoring, anomaly detection and more.
Some additional features/functions of ITTIA DB products are as follows:
Real-time analytics – ITTIA DB products are architected to offer manufacturers of embedded industrial systems a solution to process and store time series data locally in the device at the edge. They easily process transactional real-time data workloads and analytical queries to gain fast insights and perform in a wide range of environments.
Automated time series data management – ITTIA DB time-series database provides a shared context for time-stamped readings and becomes the critical pivot point for processing and understanding large volumes and workloads of IIoT data.
Ease of use – ITTIA DB’s silent installation, small footprint and elegant flexible APIs offer manufactures a way to enjoy the ease of use for adding new team members and keeping up with the complex data analytics and management required of embedded systems.
High Availability – High availability is a feature of ITTIA DB that eliminates single points of failure to ensure device data management has continuous uptime and which provides applications with constant access to the data. High availability, fault tolerance, disaster recovery, load balancing and database backup features offer peace of mind and a path to stay competitive. The ease of deploying high availability, great performance with minimal overhead of ITTIA DB provide an outstanding developer experience.
Security – ITTIA SDL, a secure development lifecycle, is conformant to the principles of IEC/ISO 62443, and ITTIA security practices assist manufacturers with advanced integrated software development methods, infused by a secure development lifecycle based on zero trust principles, enabling makers of IIoT edge devices to mitigate the vast range of potential security issues. Data encryption, authentication, and ITTIA DB Security Expert Agent Library, DB-SEAL are among the security features included with the total integration.
Performance – To manage data for real-time applications, developers have typically used specialized hardware, proprietary in-memory data storage and workarounds employing data reduction techniques. In order to fuel your high-performance applications at scale and speed, ITTIA DB offers industry leading high-performance edge data computing.
Advanced concurrency – Advanced Multi-Version Concurrency Control (MVCC) diminishes the need for database locks, resulting in fewer database access contention issues, such as deadlocks. Read access performance is greatly improved, without blocking isolated write operations.
Conclusion
Modern industrial systems, due to significantly increased software and compute power, produce vast volumes of data that must be structured, managed, analyzed and refined. ITTIA DB products are instrumental in offering the data processing and management capabilities required by modern edge IIoT systems.
Time series data has become increasingly important for building, managing and optimizing industrial systems. The ITTIA DB product portfolio plays a crucial role in enabling microcontrollers and microprocessors, as well as the Artificial Intelligence and Machine Learning engines that run on these compute platforms, to manage the vast amount of timestamped data being created.
As a result of emerging technologies like edge computing, virtualization, 5G, Machine Learning and Artificial Intelligence, IIoT edge device companies will need a comprehensive, high-performance, embedded data management capability. The ITTIA DB data management solution is built for embedded systems and IIoT devices of tomorrow and will meet these needs. Having a robust data management capability within IIoT edge devices will also open up new business opportunities and revenue streams for these manufacturers by utilizing the data already being generated by these devices.
