diff --git a/documentation/tdenginedocs-en/getting-started/index.html b/documentation/tdenginedocs-en/getting-started/index.html index 039128e9647018b83c6e565bc8be8b2fa6908335..8968441b55664cd4f76dc4493c94bc95eb3eaa4d 100644 --- a/documentation/tdenginedocs-en/getting-started/index.html +++ b/documentation/tdenginedocs-en/getting-started/index.html @@ -28,7 +28,7 @@
In the TDengine shell, you can create databases, create tables and insert/query data with SQL. Each query command ends with a semicolon. It works like MySQL, for example:
create database db;
use db;
-create table t (ts timestamp, cdata int);
+create table t (ts timestamp, speed int);
insert into t values ('2019-07-15 10:00:00', 10);
insert into t values ('2019-07-15 10:01:05', 20);
select * from t;
@@ -85,4 +85,4 @@ Query OK, 2 row(s) in set (0.001700s)
TDengine is specially designed and optimized for time-series data processing in IoT, connected cars, Industrial IoT, IT infrastructure and application monitoring, and other scenarios. Compared with other solutions, it is 10x faster on insert/query speed. With a single-core machine, over 20K requestes can be processed, millions data points can be ingested, and over 10 million data points can be retrieved in a second. Via column-based storage and tuned compression algorithm for different data types, less than 1/10 storage space is required.
Please read through the whole documentation to learn more about TDengine.
Back