mirror of
https://github.com/ClickHouse/ClickHouse.git
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44 lines
2.6 KiB
HTML
44 lines
2.6 KiB
HTML
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<div>
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<div class="container my-5 py-3">
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<div class="row mb-5">
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<div class="col-lg text-center">
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<h2>Why ClickHouse might be the right choice for you?</h2>
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</div>
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</div>
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<div class="row mb-5">
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<div class="col-lg-1">
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<img src="images/index/flash.svg" alt="Blazing fast" />
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</div>
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<div class="col-lg-5">
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<h3>Blazing fast</h3>
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<p>ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak
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processing performance for a single query stands at more than 2 terabytes per second <span class="text-muted">(after decompression, only used columns)</span>. In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency.</p>
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</div>
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<div class="col-lg-1">
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<img src="images/index/safe.svg" alt="Fault tolerant" />
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</div>
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<div class="col-lg-5">
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<h3 id="fault-tolerant">Fault tolerant</h3>
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<p>ClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows to avoid having single points of failure. Downtime of a single node or the whole datacenter won't affect the system's availability for both reads and writes.</p>
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</div>
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</div>
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<div class="row">
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<div class="col-lg-1">
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<img src="images/index/scale.svg" alt="Linearly scalable" />
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</div>
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<div class="col-lg-5">
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<h3 id="linearly-scalable">Linearly scalable</h3>
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<p>ClickHouse scales well both vertically and horizontally. ClickHouse is easily adaptable to perform either on
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cluster with hundreds or thousands of nodes, or on a single server or even on a tiny virtual machine. Currently there are installations with more multiple trillion rows or hundreds of terabytes of data per single node.</p>
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</div>
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<div class="col-lg-1">
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<img src="images/index/heart.svg" alt="Easy to use" />
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</div>
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<div class="col-lg-5">
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<h3>Easy to use</h3>
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<p>ClickHouse is simple and works out-of-the-box. It streamlines all your data processing: ingest all your structured data into the system and it becomes instantly available for building reports. SQL dialect allows to express the desired result without involving any custom non-standard API that could be found in some DBMS.</p>
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</div>
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</div>
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</div>
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</div>
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