forked from docs/doc-exports
Lu, Huayi
c5fcb46315
Reviewed-by: Hasko, Vladimir <vladimir.hasko@t-systems.com> Co-authored-by: Lu, Huayi <luhuayi@huawei.com> Co-committed-by: Lu, Huayi <luhuayi@huawei.com>
82 lines
8.2 KiB
HTML
82 lines
8.2 KiB
HTML
<a name="EN-US_TOPIC_0000001146786542"></a><a name="EN-US_TOPIC_0000001146786542"></a>
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<h1 class="topictitle1">What Are the Differences Between a Data Warehouse and the Hadoop Big Data Platform?</h1>
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<div id="body8662426"><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p1856142585513">The Hadoop big data platform can be regarded as a next-generation data warehousing system. It has the characteristics of modern data warehouses and is widely used by enterprises. Because of the scalability of MPP, the MPP-based data warehousing system is sometimes classified as a big data platform.</p>
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<p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p65615256553">However, data warehouses greatly differ from the Hadoop platform in function and user experience in different scenarios. For details, see the following table.</p>
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<div class="tablenoborder"><table cellpadding="4" cellspacing="0" summary="" id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_table198891524105517" frame="border" border="1" rules="all"><caption><b>Table 1 </b>Feature comparison between data warehouses and the Hadoop big data platform</caption><thead align="left"><tr id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_row45742575510"><th align="left" class="cellrowborder" valign="top" width="28.000000000000004%" id="mcps1.3.3.2.4.1.1"><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p1657122515519"><strong id="EN-US_TOPIC_0000001146786542__b5172078216239">Feature</strong></p>
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</th>
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<th align="left" class="cellrowborder" valign="top" width="36%" id="mcps1.3.3.2.4.1.2"><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p657325145510"><strong id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_b2863382816239">Hadoop</strong></p>
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</th>
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<th align="left" class="cellrowborder" valign="top" width="36%" id="mcps1.3.3.2.4.1.3"><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p18571251555"><strong id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_b3763873816239">Data Warehouse</strong></p>
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</th>
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</tr>
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</thead>
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<tbody><tr id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_row457192515514"><td class="cellrowborder" valign="top" width="28.000000000000004%" headers="mcps1.3.3.2.4.1.1 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p957112511551">Number of compute nodes</p>
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</td>
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<td class="cellrowborder" valign="top" width="36%" headers="mcps1.3.3.2.4.1.2 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p1057325145514">1000s</p>
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</td>
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<td class="cellrowborder" valign="top" width="36%" headers="mcps1.3.3.2.4.1.3 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p1157172525511">Max 256</p>
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</td>
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</tr>
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<tr id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_row1574257557"><td class="cellrowborder" valign="top" width="28.000000000000004%" headers="mcps1.3.3.2.4.1.1 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p6571425105514">Data volume</p>
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</td>
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<td class="cellrowborder" valign="top" width="36%" headers="mcps1.3.3.2.4.1.2 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p1057112516555">Over 10 PB</p>
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</td>
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<td class="cellrowborder" valign="top" width="36%" headers="mcps1.3.3.2.4.1.3 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p145842525520">Max 10 PB</p>
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</td>
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</tr>
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<tr id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_row2581425135513"><td class="cellrowborder" valign="top" width="28.000000000000004%" headers="mcps1.3.3.2.4.1.1 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p05818258557">Data type</p>
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</td>
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<td class="cellrowborder" valign="top" width="36%" headers="mcps1.3.3.2.4.1.2 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p1558625115517">Relational, semi-relational, unstructured (voice, images, and video)</p>
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</td>
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<td class="cellrowborder" valign="top" width="36%" headers="mcps1.3.3.2.4.1.3 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p658182515517">Relational only</p>
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</td>
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</tr>
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<tr id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_row5589253556"><td class="cellrowborder" valign="top" width="28.000000000000004%" headers="mcps1.3.3.2.4.1.1 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p1858132575518">Latency</p>
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</td>
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<td class="cellrowborder" valign="top" width="36%" headers="mcps1.3.3.2.4.1.2 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p1158425185513">Medium to high</p>
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</td>
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<td class="cellrowborder" valign="top" width="36%" headers="mcps1.3.3.2.4.1.3 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p5580256552">Low</p>
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</td>
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</tr>
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<tr id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_row458425155515"><td class="cellrowborder" valign="top" width="28.000000000000004%" headers="mcps1.3.3.2.4.1.1 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p155842535515">Application ecosystem</p>
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</td>
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<td class="cellrowborder" valign="top" width="36%" headers="mcps1.3.3.2.4.1.2 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p155842517554">Innovative/AI</p>
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</td>
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<td class="cellrowborder" valign="top" width="36%" headers="mcps1.3.3.2.4.1.3 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p9583258551">Traditional/BI</p>
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</td>
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</tr>
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<tr id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_row25820259553"><td class="cellrowborder" valign="top" width="28.000000000000004%" headers="mcps1.3.3.2.4.1.1 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p858525115514">Application development API</p>
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</td>
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<td class="cellrowborder" valign="top" width="36%" headers="mcps1.3.3.2.4.1.2 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p35882565517">SQL and other programming language APIs, such as MapReduce</p>
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</td>
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<td class="cellrowborder" valign="top" width="36%" headers="mcps1.3.3.2.4.1.3 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p258125135519">Standard database SQL</p>
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</td>
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</tr>
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<tr id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_row75832525519"><td class="cellrowborder" valign="top" width="28.000000000000004%" headers="mcps1.3.3.2.4.1.1 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p125872520553">Scalability</p>
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</td>
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<td class="cellrowborder" valign="top" width="36%" headers="mcps1.3.3.2.4.1.2 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p2058162525514">Unlimited, with comprehensive programming APIs</p>
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</td>
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<td class="cellrowborder" valign="top" width="36%" headers="mcps1.3.3.2.4.1.3 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p1858192585510">Limited, supported by UDFs</p>
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</td>
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</tr>
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<tr id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_row13581425145515"><td class="cellrowborder" valign="top" width="28.000000000000004%" headers="mcps1.3.3.2.4.1.1 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p25862535513">Transaction support</p>
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</td>
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<td class="cellrowborder" valign="top" width="36%" headers="mcps1.3.3.2.4.1.2 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p19591625195513">Limited</p>
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</td>
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<td class="cellrowborder" valign="top" width="36%" headers="mcps1.3.3.2.4.1.3 "><p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p85919256552">Comprehensive</p>
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</td>
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</tr>
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</tbody>
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</table>
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</div>
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<p id="EN-US_TOPIC_0000001146786542__en-us_topic_0000001145696609_p0595256556">Data warehouses and the Hadoop platform work together in different scenarios. GaussDB(DWS) on the public cloud can seamlessly integrate with Hadoop-based MRS on the public cloud to provide the SQL-over-Hadoop data sharing across platforms and services. GaussDB(DWS) serves as a data warehouse for managing massive data while relishing the openness, convenience, and innovation of the Hadoop platform. You can also enjoy the upper-layer applications of conventional data warehouses, especially BI applications, using GaussDB(DWS).</p>
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</div>
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<div>
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<div class="familylinks">
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<div class="parentlink"><strong>Parent topic:</strong> <a href="dws_03_0001.html">General Problems</a></div>
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</div>
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</div>
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