From a62806bdc588a29588ecd845eacabfb67144a18a Mon Sep 17 00:00:00 2001 From: Jeff Tao Date: Tue, 23 Aug 2022 21:10:39 +0800 Subject: [PATCH] Update index.md --- docs/en/02-intro/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/en/02-intro/index.md b/docs/en/02-intro/index.md index 15f58cf5c8..9f0876d297 100644 --- a/docs/en/02-intro/index.md +++ b/docs/en/02-intro/index.md @@ -39,7 +39,7 @@ By making full use of [characteristics of time series data](https://tdengine.com - **[Cloud Native](https://tdengine.com/tdengine/cloud-native-time-series-database/)**: Through native distributed design, sharding and partitioning, separation of compute and storage, RAFT, support for kubernetes deployment and full observability, TDengine is a cloud native Time-Series Database and can be deployed on public, private or hybrid clouds. -- **[Ease of Use]((https://tdengine.com/tdengine/easy-time-series-data-platform/)**: For administrators, TDengine significantly reduces the effort to[ +- **[Ease of Use](https://tdengine.com/tdengine/easy-time-series-data-platform/)**: For administrators, TDengine significantly reduces the effort to[ ](https://tdengine.com/tdengine/easy-time-series-data-platform/) deploy and maintain. For developers, it provides a simple interface, simplified solution and seamless integrations for third party tools. For data users, it gives easy data access. - **[Easy Data Analytics](https://tdengine.com/tdengine/time-series-data-analytics-made-easy/)**: Through super tables, storage and compute separation, data partitioning by time interval, pre-computation and other means, TDengine makes it easy to explore, format, and get access to data in a highly efficient way. -- GitLab