Big Data Platform Designed and Optimized for IoT
10x Faster on Insert/Query Speeds
Through the innovative design on storage, on a single-core, over 20K requests can be processed, millions of data points can be ingested, and over 10 million data points can be retrieved in a second, at least 10 times faster than general databases.
1/5 Hardware/Cloud Service Costs
Compared with typical big data solutions, no more 1/5 of computing resources are required. Via column-based storage and tuned compression algorithms for different data types, less than 1/10 of storage space is needed.
Full Stack for Time-Series Data
By integrating a database with message queuing, caching, and stream computing features together, it is no longer necessary to integrate Kafka/Redis/HBase/Spark or other software. It makes the system architecture much simpler and more robust.
Powerful Data Analysis
Whether it is 10 years or one minute ago, data can be queried just by specifying the time range. Data can be aggregated over time, over multiple time streams or both. Ad Hoc queries or analyses can be executed via the TDengine shell, Python, R or Matlab.
Seamless Integration with Other Tools
Telegraf, Grafana, Matlab, R, MQTT and other tools can be integrated with TDengine with few lines of code. OPC, Hadoop, Spark, and many others will be integrated soon.
Zero Management, No Learning Curve
It takes only seconds to download, install, and run it successfully; there are no other dependencies. Automatic partitioning on tables or DBs. SQL like syntax is adopted, together with C/C++, Python, JDBC, Go, RESTful, and Node.JS connectors.