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burmecia committed Dec 18, 2024
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32 changes: 28 additions & 4 deletions catalog/airtable/index.html
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<h1 id="airtable">Airtable</h1>
<p><a href="https://www.airtable.com">Airtable</a> is an easy-to-use online platform for creating and sharing relational databases.</p>
<p>The Airtable Wrapper allows you to read data from your Airtable bases/tables within your Postgres database.</p>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>Restoring a logical backup of a database with a materialized view using a foreign table can fail. For this reason, either do not use foreign tables in materialized views or use them in databases with physical backups enabled.</p>
</div>
<h2 id="preparation">Preparation</h2>
<p>Before you can query Airtable, you need to enable the Wrappers extension and store your credentials in Postgres.</p>
<h3 id="enable-wrappers">Enable Wrappers</h3>
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</ul>
<h2 id="query-pushdown-support">Query Pushdown Support</h2>
<p>This FDW doesn't support query pushdown.</p>
<h2 id="limitations">Limitations</h2>
<p>This section describes important limitations and considerations when using this FDW:</p>
<ul>
<li>No query pushdown support, all filtering must be done locally</li>
<li>Large result sets may experience slower performance due to full data transfer requirement</li>
<li>No support for Airtable formulas or computed fields</li>
<li>Views must be pre-configured in Airtable</li>
<li>No support for Airtable's block features</li>
<li>Materialized views using these foreign tables may fail during logical backups</li>
</ul>
<h2 id="examples">Examples</h2>
<h3 id="query-an-airtable-table">Query an Airtable table</h3>
<p>This will create a "foreign table" inside your Postgres database called <code>airtable_table</code>:</p>
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31 changes: 27 additions & 4 deletions catalog/auth0/index.html
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<h1 id="auth0">Auth0</h1>
<p><a href="https://auth0.com/">Auth0</a> is a flexible, drop-in solution to add authentication and authorization services to your applications</p>
<p>The Auth0 Wrapper allows you to read data from your Auth0 tenant for use within your Postgres database.</p>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>Restoring a logical backup of a database with a materialized view using a foreign table can fail. For this reason, either do not use foreign tables in materialized views or use them in databases with physical backups enabled.</p>
</div>
<h2 id="preparation">Preparation</h2>
<p>Before you can query Auth0, you need to enable the Wrappers extension and store your credentials in Postgres.</p>
<h3 id="enable-wrappers">Enable Wrappers</h3>
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</ul>
<h2 id="query-pushdown-support">Query Pushdown Support</h2>
<p>This FDW doesn't support query pushdown.</p>
<h2 id="limitations">Limitations</h2>
<p>This section describes important limitations and considerations when using this FDW:</p>
<ul>
<li>No query pushdown support, all filtering must be done locally</li>
<li>Large result sets may experience slower performance due to full data transfer requirement</li>
<li>Only supports the <code>users</code> object from Auth0 Management API</li>
<li>Cannot modify Auth0 user properties via FDW</li>
<li>Materialized views using these foreign tables may fail during logical backups</li>
</ul>
<h2 id="examples">Examples</h2>
<h3 id="basic-auth0-users-query">Basic Auth0 Users Query</h3>
<p>This example demonstrates querying Auth0 users data.</p>
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168 changes: 95 additions & 73 deletions catalog/bigquery/index.html
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<h1 id="bigquery">BigQuery</h1>
<p><a href="https://cloud.google.com/bigquery">BigQuery</a> is a completely serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data, with BI, machine learning and AI built in.</p>
<p>The BigQuery Wrapper allows you to read and write data from BigQuery within your Postgres database.</p>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>Restoring a logical backup of a database with a materialized view using a foreign table can fail. For this reason, either do not use foreign tables in materialized views or use them in databases with physical backups enabled.</p>
</div>
<h2 id="supported-data-types">Supported Data Types</h2>
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<th>Postgres Type</th>
<th>BigQuery Type</th>
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<td>boolean</td>
<td>BOOL</td>
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<td>bigint</td>
<td>INT64</td>
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<td>double precision</td>
<td>FLOAT64</td>
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<td>numeric</td>
<td>NUMERIC</td>
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<td>text</td>
<td>STRING</td>
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<td>varchar</td>
<td>STRING</td>
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<td>date</td>
<td>DATE</td>
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<td>timestamp</td>
<td>DATETIME</td>
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<td>timestamp</td>
<td>TIMESTAMP</td>
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<td>timestamptz</td>
<td>TIMESTAMP</td>
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</tbody>
</table>
<h2 id="preparation">Preparation</h2>
<p>Before you can query BigQuery, you need to enable the Wrappers extension and store your credentials in Postgres.</p>
<h3 id="enable-wrappers">Enable Wrappers</h3>
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<h2 id="inserting-rows-the-streaming-buffer">Inserting Rows &amp; the Streaming Buffer</h2>
<p>This foreign data wrapper uses BigQuery’s <code>insertAll</code> API method to create a <code>streamingBuffer</code> with an associated partition time. <strong>Within that partition time, the data cannot be updated, deleted, or fully exported</strong>. Only after the time has elapsed (up to 90 minutes according to <a href="https://cloud.google.com/bigquery/docs/streaming-data-into-bigquery">BigQuery’s documentation</a>), can you perform operations.</p>
<p>If you attempt an <code>UPDATE</code> or <code>DELETE</code> statement on rows while in the streamingBuffer, you will get an error of <code>UPDATE</code> or <code>DELETE</code> statement over table datasetName - note that tableName would affect rows in the streaming buffer, which is not supported.</p>
<h2 id="supported-data-types">Supported Data Types</h2>
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<thead>
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<th>Postgres Type</th>
<th>BigQuery Type</th>
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<td>boolean</td>
<td>BOOL</td>
</tr>
<tr>
<td>bigint</td>
<td>INT64</td>
</tr>
<tr>
<td>double precision</td>
<td>FLOAT64</td>
</tr>
<tr>
<td>numeric</td>
<td>NUMERIC</td>
</tr>
<tr>
<td>text</td>
<td>STRING</td>
</tr>
<tr>
<td>varchar</td>
<td>STRING</td>
</tr>
<tr>
<td>date</td>
<td>DATE</td>
</tr>
<tr>
<td>timestamp</td>
<td>DATETIME</td>
</tr>
<tr>
<td>timestamp</td>
<td>TIMESTAMP</td>
</tr>
<tr>
<td>timestamptz</td>
<td>TIMESTAMP</td>
</tr>
</tbody>
</table>
<h2 id="limitations">Limitations</h2>
<p>This section describes important limitations and considerations when using this FDW:</p>
<ul>
<li>Large result sets may experience network latency during data transfer</li>
<li>Data in streaming buffer cannot be modified for up to 90 minutes</li>
<li>Only supports specific data type mappings between Postgres and BigQuery</li>
<li>Materialized views using foreign tables may fail during logical backups</li>
</ul>
<h2 id="examples">Examples</h2>
<p>Some examples on how to use BigQuery foreign tables.</p>
<p>Let's prepare the source table in BigQuery first:</p>
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