[Technology Outlook] GBase: Research and Practice on IoT Spatiotemporal Big Data

On March 30, the 2017 Spatial Information Enterprise Development Forum was held in Yixing, Jiangsu Province. Wang Zengning, Secretary-General of the China Geographic Information Industry Association, and Li Guangqian, Division Director of the Information Center of the Development Research Center of the State Council, attended the meeting along with other leaders and experts. The conference discussed the development of national informatization during the 13th Five-Year Plan period, new directions for industrial transformation, the development direction of geographic information industry enterprises, and how to create a sustainable spatial information industry ecosystem.

GBase was invited to the conference and presented "IoT Spatiotemporal Big Data Research and Practice," which attracted the attention of attending experts and scholars.

The GIS Industry Enters the Big Data Era

With the rise of the Internet of Things, IoT applications are penetrating various industries. In particular, smart cities, smart agriculture, smart transportation, energy monitoring, environmental monitoring, and safety production have already seen many successful cases. Most IoT applications provide holistic solutions based on GIS platforms. GIS applications in the IoT era have the following characteristics:

Massive numbers of smart device objects collect a large volume of real-time sensor data. At the same time, a type of dynamic GIS trajectory data — where device locations change continuously over time — constitutes spatiotemporal big data. Beyond real-time monitoring on GIS platforms, big data applications increasingly require leveraging massive historical data to unlock the value of cold data and make it active, leading to widespread big data analysis scenarios.

Ultimately, it all comes down to data! The GIS industry is entering the big data era! However, due to the unique nature of GIS data, existing technologies face significant challenges in managing GIS big data:

● Diverse data types — structured data, unstructured data, and GIS data.

● Application complexity — real-time monitoring and historical data analysis.

● Data transmission — issues such as transmission interruptions and data loss.

● Horizontal scalability — a single server can no longer meet performance scaling requirements, necessitating a distributed, cloud-native deployment solution with horizontal scaling capabilities.

GBase provides exactly such a solution.

GBase IoT Spatiotemporal Big Data Holistic Solution

IoT Spatiotemporal Big Data Holistic Solution: From Devices to a Distributed, Converged Big Data Processing Platform

Smart Devices: Pushing Cognition to the Edge

Integrate the GBase 8e embedded database into smart devices to store and manage real-time sensor data. Build intelligent edge devices and applications that resolve data upload issues while providing richer front-end solutions.

As an embedded database, GBase 8e features minimal resource consumption (only 64 MB of memory and 128 MB of storage), high stability, self-management with zero maintenance, and enterprise-grade general relational database capabilities, including strong transaction consistency, JDBC/ODBC interfaces, and standard SQL.

Big Data Processing: Distributed Full-Data Processing

A distributed, converged big data management layer — GBaseUP — is employed.

GBaseUP seamlessly and organically integrates the traditional OLTP database GBase 8t, the MPP OLAP database GBase 8a, and the Hadoop ecosystem, fully leveraging the value of each system to achieve unified management of spatiotemporal data, structured and unstructured data, and hot and warm data. GBaseUP consolidates heterogeneous data processing engines under a unified super SQL engine, providing upper-layer applications with a uniform SQL interface and real-time data synchronization between engines, thereby solving the data processing challenges of the IoT era.

Key Technology: Spatiotemporal Data Storage Model

Targeting the characteristics of GIS spatial data and the time-series nature of IoT sensor data, a key technological innovation has been made: the spatiotemporal data storage model, which organically combines spatial data and time-series data, improving processing performance by 25 to 100 times.

Driven by the development needs of the IoT industry and through continuous product and technology innovation, GBase offers a holistic IoT spatiotemporal big data solution, providing a solid foundation for GIS industry customers and partners to tackle the challenges of IoT big data management.