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[docs] Replace "Compaction Service" to "Tiering Service" in all images (#576)
* [docs] Update "Compaction Service" to "Tiering Service" in images * fix (cherry picked from commit 00bf675)
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website/docs/install-deploy/overview.md

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@@ -10,7 +10,7 @@ Below, we provide an overview of the key components of a Fluss cluster, detailin
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The figure below shows the building blocks of Fluss clusters:
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<img width="1200px" src={require('./deployment_overview.png').default} />
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<img width="1200px" src={require('../assets/deployment_overview.png').default} />
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website/docs/maintenance/tiered-storage/overview.md

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The overall tiered storage architecture is shown in the following diagram:
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<img width="600px" src={require('./tiered-storage.png').default} />
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<img width="600px" src={require('../../assets/tiered-storage.png').default} />

website/docs/streaming-lakehouse/overview.md

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With [Lakehouse Storage](maintenance/tiered-storage/lakehouse-storage.md), Fluss unifies data streaming and data Lakehouse by serving real-time streaming data on top of Lakehouse.
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This not only brings low latency to data Lakehouse, but also adds powerful analytics to data streams.
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In order to build Streaming Lakehouse, Fluss maintains a compaction service to compact the real-time data in Fluss cluster into Lakehouse storage.
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To build a Streaming Lakehouse, Fluss maintains a tiering service that compacts real-time data from the Fluss cluster into the data lake format stored in the Lakehouse Storage.
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The data in Fluss cluster (streaming Arrow format) is write-optimized for low-latency read and write, and the compacted data in Lakehouse (Parquet format with compressions) is read-optimized for powerful analytics and space-optimized for storing long-term data.
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So the data in Fluss cluster serves real-time data layer which retains days with sub-second-level freshness, and the data in Lakehouse serves historical data layer which retains months with minute-level freshness.
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![streamhouse](streamhouse.png)
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![streamhouse](../assets/streamhouse.png)
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The core idea of Streaming Lakehouse is shared data and shared metadata between stream and Lakehouse, avoiding data duplication and metadata inconsistency.
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Some powerful features it provided are:
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website/static/img/fluss.png

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