TSQL is a structured query language for time series data, which is provided by Time Series Database (TSDB). TSQL allows you to use the SQL syntax to read data. This provides an easy method to access data and use enhanced compute capabilities. This topic describes the key features and benefits of TSQL.
TSQL can convert time series data into structured data by mapping metrics to relational data tables and mapping tags, metric values, and timestamps to corresponding columns in a relational database. You can create SQL query statements where the tables and columns are specified to query, filter, and compute time series data.
OpenTSDB is an open source database service that allows you to query time series data only by using RESTful API operations. This results in high adoption costs and inconvenience. TSQL provides a more simple method of querying data than OpenTSDB. TSQL also offers an easy method for SQL developers to develop time series databases.
You can use TSQL to perform JOIN operations for association analysis. This allows you to query data that has the same tag and timestamp. TSQL also allows you to query multiple metrics and join the metric values in the query results.
OpenTSDB is an open source database service that allows you to query only one metric in each subquery. You cannot use OpenTSDB to query multiple metrics for association analysis. To query multiple metrics for association analysis in TSQL, you must align timestamps and time series data. TSQL provides an easy method of querying multiple metrics. If you use TSQL to query multiple metrics, TSQL automatically aligns timestamps and time series data. This helps you reduce service development costs and meet the business requirements of querying multiple metrics.
TSQL enhances the computing capabilities of the standard SQL. TSQL is compatible with native SQL functions, and supports time precision functions that are specific to time series data. You can use these time precision functions to downsample and aggregate data.
TSQL allows you to perform complex computing on multiple columns. You can perform computing on multiple fields of metrics when you query data from databases. This helps you meet your complex computing requirements.