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new d5dd4a42e [INLONG-4698][Doc] Update the definitions and features to
make them accurate (#4699)
d5dd4a42e is described below
commit d5dd4a42e922c51e0384f61ca08627ca7e5b10af
Author: Charles Zhang <[email protected]>
AuthorDate: Sat Jun 18 21:14:46 2022 +0800
[INLONG-4698][Doc] Update the definitions and features to make them
accurate (#4699)
---
README.md | 14 +++++++-------
1 file changed, 7 insertions(+), 7 deletions(-)
diff --git a/README.md b/README.md
index 62d8d1bb3..cad1a4276 100644
--- a/README.md
+++ b/README.md
@@ -41,9 +41,9 @@
# What is Apache InLong?
[Apache InLong](https://inlong.apache.org)(incubating) is a one-stop
integration framework for massive data that provides automatic, secure and
reliable data transmission capabilities. InLong supports both batch and stream
data processing at the same time, which offers great power to build data
analysis, modeling and other real-time applications based on streaming data.
-InLong (应龙) is a divine beast in Chinese mythology who guides river into the
sea, it is regarded as a metaphor of the InLong system for reporting streams of
data.
+InLong (应龙) is a divine beast in Chinese mythology who guides the river into
the sea, and it is regarded as a metaphor of the InLong system for reporting
data streams.
-InLong was originally built at Tencent, which has served online businesses for
more than 8 years, to support massive data (data scale of more than 40 trillion
pieces of data per day) reporting services in big data scenarios. The entire
platform has integrated 5 modules: Ingestion, Convergence, Caching, Sorting,
and Management, so that the business only needs to provide data sources, data
service quality, data landing clusters and data landing formats, that is, the
data can be continuous [...]
+InLong was originally built at Tencent, which has served online businesses for
more than 8 years, to support massive data (data scale of more than 80 trillion
pieces of data per day) reporting services in big data scenarios. The entire
platform has integrated 5 modules: Ingestion, Convergence, Caching, Sorting,
and Management, so that the business only needs to provide data sources, data
service quality, data landing clusters and data landing formats, that is, the
data can be continuous [...]
For getting more information, please visit our project documentation at
https://inlong.apache.org/
<img
src="https://github.com/apache/incubator-inlong-website/blob/master/static/img/inlong-structure-en.png";
align="center" alt="Apache InLong"/>
@@ -51,11 +51,11 @@ For getting more information, please visit our project
documentation at https://
## Features
Apache InLong offers a variety of features:
-* **Ease of Use**: a SaaS-based service platform, you can easily and quickly
report, transfer, and distribute data by publishing and subscribing to data
based on topics.
-* **Stability & Reliability**: derived from the actual online production
environment, it delivers high-performance processing capabilities for 10
trillion-level data streams and highly reliable services for 100 billion-level
data streams.
-* **Comprehensive Features**: supports various types of data access methods
and can be integrated with different types of Message Queue (MQ) services, it
also provides real-time data extract, transform, and load (ETL) and sorting
capabilities based on rules, allows you to plug features to extend system
capabilities.
-* **Service Integration**: provides unified system monitoring and alert
services, it provides fine-grained metrics to facilitate data visualization,
you can view the running status of queues and topic-based data statistics in a
unified data metric platform, configure the alert service based on your
business requirements so that users can be alerted when errors occur.
-* **Scalability**: adopts a pluggable architecture that allows you to plug
modules into the system based on specific protocols, so you can replace
components and add features based on your business requirements
+* **Ease of Use**: a SaaS-based service platform. Users can easily and quickly
report, transfer, and distribute data by publishing and subscribing to data
based on topics.
+* **Stability & Reliability**: derived from the actual online production
environment. It delivers high-performance processing capabilities for 10
trillion-level data streams and highly reliable services for 100 billion-level
data streams.
+* **Comprehensive Features**: supports various types of data access methods
and can be integrated with different types of Message Queue (MQ). It also
provides real-time data extract, transform, and load (ETL) and sorting
capabilities based on rules. InLong also allows users to plug features to
extend system capabilities.
+* **Service Integration**: provides unified system monitoring and alert
services. It provides fine-grained metrics to facilitate data visualization.
Users can view the running status of queues and topic-based data statistics in
a unified data metric platform. Users can also configure the alert service
based on their business requirements so that users can be alerted when errors
occur.
+* **Scalability**: adopts a pluggable architecture that allows you to plug
modules into the system based on specific protocols. Users can replace
components and add features based on their business requirements.
## When should I use InLong?
![https://github.com/apache/incubator-inlong-website/blob/master/static/img/inlong-structure-en.png"](https://github.com/apache/incubator-inlong-website/blob/master/static/img/inlong-structure-en.png"){kind=link}