The user can easily simulate the scenario of a large number of devices generating a very large amount of data. In addition, it supports query and subscription testing.
TDengine demonstrates excellent performance, 1: The writing speed can reach 12,000 to 13,000 records per second; 2: Storage spaces required for storing location data are only 1/7 of the former solution; 3: Querying the data from a single device by one-day interval will respond within 0.1 seconds.
TDengine serves as a solution for monitoring in the HeyGears 3D pringting system. The problems we’ve encountered in Hadoop system can be easily solved with its simple SQL-like syntax.
TDengine currently performs as a highly efficient time-series database in POIZON. It’s very easy to manage the cluster. In addition, it lowers the operation and maintenance costs a lot.
Baffled by numerous pain points, RisingStar IoT Platform chose TDengine, a high-performance time-series database, to upgrade their data processing solution.
Through comparative research on the solutions provided by several prevailing time-series databases such as IoTDB, Druid, ClickHouse, and TDengine, SF Technology finally decided to choose TDengine as a solution. Since using TDengine, impressive improvements have been achieved in the terms of stability and writing/query performance.
In this test, TDengine is compared with OpenTSDB in the terms of writing throughput, query throughput, aggregation query response time and on-disk compression. The results demonstrates that TDengine outperforms OpenTSDBwith 25x greater write throughput, 32x larger query throughput, 1000x faster in aggregation query (1000x when grouping by tags and 40x when grouping by time) while using 5x less disk space.
In this test, TDengine is compared with Cassandra in the terms of writing throughput, data ingestion, aggregation query response time and on-disk compression. The results demonstrates that TDengine outperforms Cassandra with 20x greater write throughput, 17x larger data ingestion, 4000x faster in aggregation query (2500x when grouping by tags and 119x when grouping by time) while using 26.7x less disk space.
In this test, TDengine is compared with InfluxDB in the terms of writing throughput, query throughput, aggregation query response time and on-disk compression. The result demonstrates that TDengine outperforms InfluxDB with 5x greater write throughput, 35x larger query throughput, 140x faster in aggregation query (250x when grouping by tags and 12x when grouping by time) while using 2.1x less disk space.
TDengine is a light, high-efficient, single-node open-source and IOT-oriented data processing engine. As a data engine designed for IOT, TDengine has huge advantages in writing, querying, storage, etc. In this article, we will talk about the architecture and storage design of TDengine to help users to fully understand it.