LadyForest commented on code in PR #159:
URL: https://github.com/apache/flink-table-store/pull/159#discussion_r898813837
##########
docs/content/docs/development/overview.md:
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@@ -26,9 +26,27 @@ under the License.
# Overview
-Flink Table Store is a unified streaming and batch store for building dynamic
-tables on Apache Flink. Flink Table Store serves as the storage engine behind
-Flink SQL Managed Table.
+Flink Table Store is a unified storage to build dynamic tables for both
streaming and
+batch processing in Flink, supporting high speed data ingestion and timely
data query.
+
+## Architecture
+
+<center>
+<img src="/img/architecture.png" width="100%"/>
+</center>
+
+As shown in the architecture above:
+
+* Users can use Flink to insert data into the Table Store, either by streaming
the change log
+ captured from databases, or by loading the data in batches from the other
stores like data warehouses.
Review Comment:
```suggestion
* **Consumption Mode** Table Store supports a versatile way to read/write
data and perform OLAP queries.
- For reads, it supports consuming data <1> from historical snapshots (in
batch mode), <2>from the latest offset (in continuous mode), or <3> reading
incremental snapshots in a hybrid way.
- For writes, it supports streaming synchronization of the changelog of
databases(CDC) or bulk load the tables from other data warehouses.
OLAP queries are supported either in streaming or batch mode.
* **Ecosystem** In addition to Apache Flink, Table Store also supports
read/write by other computation engines like Apache Hive.
* **Internal** Under the hood, table Store uses a hybrid storage
architecture with a lakehouse format to store historical data and a queue
system to store incremental data. The former stores the columnar files on the
filesystem/object-store and uses the LSM tree structure to support a large
volume of data updates and high-performance queries. The latter uses Apache
Kafka to capture data in real-time[1].
[1] https://kafka.apache.org/intro
```
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