In recent years, China's new energy vehicles have developed rapidly and performed well in global competition, and have maintained the world's No. 1 sales volume for eight consecutive years. Driven by emerging technologies, the digital transformation of new energy vehicles is also accelerating, from automobile manufacturing to energy utilization, human-computer interaction, all links are undergoing digital transformation, and the improvement of basic software capabilities and the collaboration of software and hardware have become the key to the digital upgrade of automobiles.
In this context, on December 15, the "CIAS 2023 China New Energy Vehicle Industry Digital Intelligence Annual Conference" was held in Hefei, China, and this conference gathered more than 220 representatives and more than 120 professional guests at home and abroad to focus on the digital transformation of the automotive industry from multiple angles and all-round in-depth analysis, and jointly improve the development and future of China's digital intelligence vehicles. Tao Jianhui, founder & core developer of TDengine, was invited to attend the annual meeting and share the theme of "how to quickly build a high-performance big data platform to cope with the rapidly changing new energy market".
Tao Jianhui pointed out that in the digital transformation of the automotive industry, it usually uses open-source big data software such as Kafka, Redis, HBase, MongoDB, Cassandra, ES, Hadoop, Spark, and ZooKeeper to build a data processing platform and process massive data through clusters. However, this practice often leads to problems such as low development efficiency, poor operational efficiency, complex O&M, and slow time to market. For new energy vehicles, the data generated by them has typical time series data characteristics, so building a high-performance data platform with time series database function is the key to solving the problem. Tao Jianhui took the high-performance, distributed Internet of Things and industrial big data platform TDengine as an example to introduce the capabilities of the new generation of industrial data processing software, and shared the results achieved by new energy vehicle companies in transforming data architectures in practical applications.
The problem pointed out by Tao Jianhui has appeared in the data processing of Leapmotor. They previously stored time series data in MongoDB and HBase, respectively. However, MongoDB stores all data in memory, resulting in high storage costs and only a limited amount of timeIn addition, the stored data format needs to be processed by the business organization, which is not only inflexible for business changes, but also very limited for the business that can be implemented. HBase, on the other hand, is used to store some real-time signals, which requires the support of a complete set of HDFS, and the use, O&M, and labor costs are very high, requiring big data-related talents to ensure smooth operation. In order to reduce costs and improve efficiency, Leapmotor decided to try TDengine on the new C11 model, and the effect has been significantly improved: in terms of query, TDengine's columnar storage can directly use SQL computing, and it is no longer necessary to process data before querying like MongoDBAt the same time, TDengine's high compression algorithm also improves the compression performance by 10-20 times, which not only saves storage space, but also solves the problem of high storage costs.
It is worth mentioning that at the award ceremony of the "CIAS 2023 EV Billboard", TDENGINE won the "Annual New Energy Vehicle Big Data Product Innovation Award" at the award ceremony of the "CIAS 2023 EV Billboard". It is understood that "CIAS 2023" aims to explore enterprises, products and people with benchmarking significance and best practices in the new energy vehicle industry, set a benchmark for the development of the industry, provide high-quality cases for technological innovation, and open up new opportunities for business cooperation.
Finally, the TDENGINE booth at the annual meeting was still one of the most popular booths, attracting a large number of listeners to come and communicate. Let's take a look at the lively atmosphere