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<title>Distributed SQL</title>

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<span id="openzim-page-title" class="mw-page-title-main"><span class="mw-page-title-main">Distributed SQL</span></span>

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<p>A <b>distributed SQL</b> database is a single <a href="Relational_database" title="Relational database">relational database</a> which replicates data across multiple servers. Distributed SQL databases are strongly consistent and most support consistency across racks, data centers, and <a href="Wide_area_network" title="Wide area network">wide area networks</a> including cloud availability zones and cloud geographic zones. Distributed SQL databases typically use the <a href="Paxos_(computer_science)" title="Paxos (computer science)">Paxos</a> or <a href="Raft_(algorithm)" title="Raft (algorithm)">Raft</a> algorithms to achieve <a href="Consensus_decision-making" title="Consensus decision-making">consensus</a> across multiple nodes.

</p><p>Sometimes distributed SQL databases are referred to as <a href="NewSQL" title="NewSQL">NewSQL</a> but NewSQL is a more inclusive term that includes databases that are not <a href="Distributed_databases" class="mw-redirect" title="Distributed databases">distributed databases</a>.

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<div class="mw-heading mw-heading2"><h2 id="History">History</h2></div>

<p><a href="Google" title="Google">Google</a>'s <a href="Spanner_(database)" title="Spanner (database)">Spanner</a> popularized the modern distributed SQL database concept. Google described the database and its architecture in a 2012 whitepaper called "Spanner: Google's Globally-Distributed Database." The paper described Spanner as having evolved from a <a href="Big_Table" class="mw-redirect" title="Big Table">Big Table</a>-like <a href="Key_value" class="mw-redirect" title="Key value">key value</a> store into a temporal multi-version database where data is stored in "schematized semi-relational tables."<sup id="cite_ref-autogenerated1_1-0" class="reference"><a href="#cite_note-autogenerated1-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup>

</p><p>Spanner uses atomic clocks with the Paxos algorithm to accomplish consensus with regards to state distributed between servers. In 2010, and earlier implementation, <a href="Clustrix" title="Clustrix">ClustrixDB</a> (now <a href="MariaDB" title="MariaDB">MariaDB</a> Xpand) moved from a hardware appliance to a Paxos-based software database<sup id="cite_ref-2" class="reference"><a href="#cite_note-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup> and was later acquired by <a href="MariaDB" title="MariaDB">MariaDB</a><sup id="cite_ref-3" class="reference"><a href="#cite_note-3"><span class="cite-bracket">[</span>3<span class="cite-bracket">]</span></a></sup> and added to a <a href="SaaS" class="mw-redirect" title="SaaS">SaaS</a> cloud offering called <a href="MariaDB#SkySQL" title="MariaDB">SkySQL</a>.<sup id="cite_ref-4" class="reference"><a href="#cite_note-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup> In 2015, two Google engineers left the company to create <a href="Cockroach_Labs" class="mw-redirect" title="Cockroach Labs">Cockroach DB</a> which achieves similar results using the Raft algorithm without atomic clocks or custom hardware.<sup id="cite_ref-5" class="reference"><a href="#cite_note-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup>

</p><p>Spanner is primarily used for transactional and time-series use cases. However, Google furthered this research with a follow on paper about Google F1 which it describes as a <a href="Hybrid_transactional/analytical_processing" title="Hybrid transactional/analytical processing">Hybrid transactional/analytical processing</a> database built on Spanner.<sup id="cite_ref-autogenerated1_1-1" class="reference"><a href="#cite_note-autogenerated1-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup>

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<div class="mw-heading mw-heading2"><h2 id="Architecture">Architecture</h2></div>

<p>Distributed SQL databases have the following general characteristics:

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<ul><li>synchronous replication</li>

<li>strong transactional consistency across at least availability zones (i.e. <a href="ACID" title="ACID">ACID</a> compliance)<sup id="cite_ref-6" class="reference"><a href="#cite_note-6"><span class="cite-bracket">[</span>6<span class="cite-bracket">]</span></a></sup></li>

<li>relational database front end structure – meaning data represented as tables with rows and columns similar to any other <a href="RDBMS" class="mw-redirect" title="RDBMS">RDBMS</a></li>

<li>automatically <a href="Shard_(database_architecture)" title="Shard (database architecture)">sharded</a> data storage</li>

<li>underlying key–value storage<sup id="cite_ref-7" class="reference"><a href="#cite_note-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-autogenerated1_1-2" class="reference"><a href="#cite_note-autogenerated1-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup></li>

<li>native SQL implementation</li></ul>

<p>Following the <a href="CAP_Theorem" class="mw-redirect" title="CAP Theorem">CAP Theorem</a>, distributed SQL databases are "CP" or consistent and partition-tolerant. Algorithmically they sacrifice availability in that a failure of a primary node can make the database unavailable for writes.

</p><p>All distributed SQL implementations require some kind of temporal synchronization to guarantee consistency. With the exception of Spanner, most do not use custom hardware to provide atomic clocks. Spanner is able to synchronize writes with temporal guarantees. Implementations without custom hardware require servers to compare clock offsets and potentially retry reads.<sup id="cite_ref-8" class="reference"><a href="#cite_note-8"><span class="cite-bracket">[</span>8<span class="cite-bracket">]</span></a></sup>

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<div class="mw-heading mw-heading2"><h2 id="Distributed_SQL_implementations">Distributed SQL implementations</h2></div>

<th>Vendor</th>

<th>API

</th>

<th>License model

</th></tr>

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<td><a href="Amazon_Aurora" title="Amazon Aurora">Amazon Aurora</a></td>

<td><a href="PostgreSQL" title="PostgreSQL">PostgreSQL</a> & <a href="MySQL" title="MySQL">MySQL</a>

</td>

<td>Proprietary

</td></tr>

<tr>

<td><a href="CockroachDB" title="CockroachDB">CockroachDB</a>

</td>

<td><a href="PostgreSQL" title="PostgreSQL">PostgreSQL</a>-like

</td>

<td>Proprietary

</td></tr>

<tr>

<td><a href="Spanner_(database)" title="Spanner (database)">Google Spanner</a></td>

<td>Proprietary SQL-like

</td>

<td>Proprietary

</td></tr>

<tr>

<td><a href="MySQL_Cluster" title="MySQL Cluster">MySQL Cluster</a></td>

<td><a href="MySQL" title="MySQL">MySQL</a>

</td>

<td>Open Source (GPLv2)

</td></tr>

<tr>

<td><a href="NuoDB" title="NuoDB">NuoDB</a></td>

<td>Proprietary SQL

</td>

<td>Proprietary

</td></tr>

<tr>

<td><a href="YugabyteDB" title="YugabyteDB">YugabyteDB</a></td>

<td><a href="PostgreSQL" title="PostgreSQL">PostgreSQL</a> & <a href="Apache_Cassandra" title="Apache Cassandra">Cassandra</a> CQL-like

</td>

<td>Open Source (Apache 2.0)

</td></tr>

<tr>

</td>

<td><a href="MySQL" title="MySQL">MySQL</a>-like

</td>

<td>Open Source (Apache 2.0)

</td></tr>

<tr>

<td><a href="MariaDB" title="MariaDB">MariaDB XPand</a>

</td>

<td><a href="MariaDB" title="MariaDB">MariaDB</a>

</td>

<td>Proprietary

</td></tr>

<tr>

<td><a href="Teradata" title="Teradata">Teradata</a></td>

<td>Proprietary SQL-like

</td>

<td>Proprietary

</td></tr>

<tr>

<td>Proprietary SQL-like, <a href="PostgreSQL" title="PostgreSQL">PostgreSQL</a>-like

</td>

<td>Open Source (Apache 2.0)

</td></tr></tbody></table>

<div class="mw-heading mw-heading2"><h2 id="Compared_to_NewSQL">Compared to NewSQL</h2></div>

<p>CockroachDB, YugabyteDB and others have at times referred to themselves as <a href="NewSQL" title="NewSQL">NewSQL</a> databases. Some of the NewSQL databases have fundamentally different architectures, but were cited as examples of NewSQL by Matthew Aslett who coined the term.<sup id="cite_ref-10" class="reference"><a href="#cite_note-10"><span class="cite-bracket">[</span>10<span class="cite-bracket">]</span></a></sup> In essence, distributed SQL databases are built from the ground-up and NewSQL databases include replication and sharding technologies added to existing client-server relational databases like <a href="PostgreSQL" title="PostgreSQL">PostgreSQL</a>.<sup id="cite_ref-11" class="reference"><a href="#cite_note-11"><span class="cite-bracket">[</span>11<span class="cite-bracket">]</span></a></sup> Some experts define DistributedSQL databases as a more specific subset of NewSQL databases.<sup id="cite_ref-12" class="reference"><a href="#cite_note-12"><span class="cite-bracket">[</span>12<span class="cite-bracket">]</span></a></sup>

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<div class="mw-heading mw-heading2"><h2 id="References">References</h2></div>

<li id="cite_note-autogenerated1-1"><span class="mw-cite-backlink">^ <a href="#cite_ref-autogenerated1_1-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-autogenerated1_1-1"><sup><i><b>b</b></i></sup></a> <a href="#cite_ref-autogenerated1_1-2"><sup><i><b>c</b></i></sup></a></span> <span class="reference-text"><a rel="nofollow" class="external free" href="https://storage.googleapis.com/pub-tools-public-publication-data/pdf/41344.pdf">https://storage.googleapis.com/pub-tools-public-publication-data/pdf/41344.pdf</a> </span>

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