From 2470e3f57ccdbb53214216b3176fcc13366a10aa Mon Sep 17 00:00:00 2001 From: Hongze Cheng Date: Tue, 6 Aug 2019 11:20:32 +0800 Subject: [PATCH] Fix #281 --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 35a192d148..c82cda6f3c 100644 --- a/README.md +++ b/README.md @@ -8,7 +8,7 @@ TDengine is an open-sourced big data platform under [GNU AGPL v3.0](http://www.g - **1/5 Hardware/Cloud Service Costs**: Compared with typical big data solutions, less than 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.. +- **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, multiple time streams or both. Ad Hoc queries or analyses can be executed via TDengine shell, Python, R or Matlab. -- GitLab