The TDengine Server and Client can now be run on x64 systems that are running macOS, Windows 10 and 11, Windows Server 2016 and 2019, CentOS 7.9 and 8, or Ubuntu 18 and 20, as well as ARM64 systems running macOS or CentOS. For the latest information on operating system support, see the documentation.
Join us today in celebrating the release of the TDengine Database PI Connector! The connector is a simple but powerful solution that allows PI customers to build a hybrid system leveraging their existing investment in PI while preparing a path forward to expand data historians and make use of modern analytics products.
With version 3.0.1.5, TDengine Database offers support for macOS in addition to Linux and Windows. You can now test your applications more efficiently and connect to a TDengine Server running on any operating system from your own MacBook.
TDengine suggests to use the globally unique ID of data collection point as a table name (such as device serial number). However, in some scenarios, there is no unique ID, and multiple IDs can be combined into a unique ID. It is not recommended to use a unique ID as tag value.
The Top 50 Most Promising Startups is a yearly collection of up-and-coming enterprises in fields such as data, fintech, and cybersecurity that are considered by industry sources to have the most potential for future growth and valuation.
Digital Transformation Easier Than Ever
Getting started with TDengine is easier than any other time series database – you can register for a free TDengine Cloud account at cloud.tdengine.com (no credit card required) and see for yourself before making a decision.
TDengine Cloud is a fully managed, enterprise-ready cloud solution that saves you time by taking care of database management tasks like clustering, backup, and data retention on its own.
You can get the difference between the maximum and minimum values of a column by using the SPREAD function. Note that you can always constrain the time spans by using a WHERE clause on the timestamp field.
Note: At present, TDengine does not technically restrict the use of a STable of a database (dbA) as a template to create a sub-table of another database (dbB). This usage will be prohibited later, and it is not recommended to use this method to create a table.
Today TDengine Database , the open-source, cloud-native time-series database (TSDB) optimized for IoT, was named one of the Top 50 Most Promising Startups by tech sector-oriented media organization The Information.
TDengine is a popular open-source data platform purpose-built for time-series data. With over 19,000 stars on GitHub and hundreds of new running instances daily, TDengine is used in over 50 countries worldwide. The company has raised $69M in venture capital, including a $47M 2021 series B round from MatrixPartners China, Sequoia Capital China, GGV Capital, and Index Capital.
"I’m thrilled to see that TDengine has been selected as one of the most promising startups," said Jeff Tao, founder and core developer of TDengine. "This is another indication that industry insiders understand the potential of TDengine to power modern data workflows in IoT and other rapidly growing markets. I’m confident that TDengine is well positioned to continue making technical as well as business breakthroughs going forward."
CREATE STABLE meters (ts TIMESTAMP, current FLOAT, voltage INT, phase FLOAT) TAGS (location BINARY(64), groupId INT);
Note: The STABLE keyword in this instruction needs to be written as TABLE in versions before 2.0.15.
SELECT ts, MAVG(pm25,168) FROM weather.p1;
TDengine also provides a HISTOGRAM function, which we could use to see how many measurements fall into the good, unhealthy, very unhealthy, and hazardous categories. We can look at this on a yearly basis to see whether the air quality is getting better. The HISTOGRAM function returns a table/grid.
Unlock your data with an open system: Now that your data is in the cloud, you have access to all kinds of modern tools for analytics and visualization. For example, the official TDengine plug-in for Grafana enables new levels of observability and visualization for your data with a range of premade and customizable dashboards.
TDengine also provides connectors for a variety of programming languages that make integration with your favorite tools fast and convenient.
Each type of data collection point needs an established STable, so an IoT system often has multiple STables. For the power grid, we need to build a STable for smart meters, transformers, buses, switches, etc. For IoT, a device may have multiple data collection points (for example, a fan for wind-driven generator, some collection points capture parameters such as current and voltage, and some capture environmental parameters such as temperature, humidity and wind direction). In this case, multiple STables need to be established for corresponding types of devices. All collected physical metrics contained in one and the same STable must be collected at the same time (with a consistent timestamp).
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