PG variable (#4214)

Author: atovpeko

.github/styles/Google/Headings.yml

@@ -41,7 +41,7 @@ exceptions:
   - NFT
   - pgAdmin
   - PgVectorizer
-  - PostgreSQL
+  - Postgres
   - Prometheus
   - Promscale
   - Promscale Connector

.github/styles/Google/WordList.yml

@@ -45,7 +45,7 @@ swap:
   master: primary
   network IP address: internal IP address
   open-source: open source
-  Postgres: PostgreSQL
+  PostgreSQL: Postgres
   Promscale connector: Promscale Connector
   quickstart: quick start
   regex: regular expression

.github/styles/Vocab/Timescale/accept.txt

@@ -93,7 +93,7 @@ pg_restore
 Plotly
 pre
 POSIX
-PostgreSQL
+Postgres
 [Pp]ooler?
 Prometheus
 PromLens

.github/styles/config/vocabularies/Timescale/accept.txt

@@ -94,7 +94,7 @@ pg_restore
 Plotly
 pre
 POSIX
-PostgreSQL
+Postgres
 [Pp]ooler?
 Prometheus
 PromLens

CONTRIBUTING.md

@@ -146,7 +146,7 @@ To make a documentation page more visible and clear for Google:
 - Include main page keywords into the meta tags, page title, first header, and intro. These are usually the names of features described in the page. For example, for a page dedicated to creating hypertables, you can use the keyword **hypertable** in the following way: 
 
    - Title: Create a hypertable in Tiger Cloud
-   - Description: Turn a regular PostgreSQL table into a hypertable in a few steps, using Tiger Cloud Console. 
+   - Description: Turn a regular $PG table into a hypertable in a few steps, using Tiger Cloud Console. 
    - First header: Create a hypertable
 
 ## Docs for deprecated products

README.md

@@ -8,7 +8,7 @@
 
 <div align=center>
 
-<h3>Tiger Cloud is the modern PostgreSQL data platform for all your applications. It enhances PostgreSQL to handle time series, events, real-time analytics, and vector search—all in a single database alongside transactional workloads.
+<h3>Tiger Cloud is the modern Postgres data platform for all your applications. It enhances Postgres to handle time series, events, real-time analytics, and vector search—all in a single database alongside transactional workloads.
 </h3>
 
 [![Docs](https://img.shields.io/badge/Read_the_TigerData_docs-black?style=for-the-badge&logo=readthedocs&logoColor=white)](https://docs.tigerdata.com/)
@@ -47,9 +47,9 @@ See the [Contributing guide](CONTRIBUTING.md) for style and language guidance.
 
 ## Learn about TigerData
 
-TigerData is PostgreSQL made powerful. To learn more about the company and its products, visit [tigerdata.com](https://www.tigerdata.com).
+TigerData is Postgres made powerful. To learn more about the company and its products, visit [tigerdata.com](https://www.tigerdata.com).
 
 [docs-issues]: https://github.com/timescale/docs/issues
 [github-fork]: https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/fork-a-repo
 [github-clone]: https://docs.github.com/en/repositories/creating-and-managing-repositories/cloning-a-repository
-[gatsby]: https://www.gatsbyjs.com/
+[gatsby]: https://www.gatsbyjs.com/

_code-samples/toolkit/stats_agg-one-variable.md

@@ -18,7 +18,7 @@ see [Statistical Aggregates (2D)](./stats_agg_2D.md).
 In order to make common statistical aggregates easier to work with in window
 functions and continuous aggregates, Toolkit provides common statistical
 aggregates in a slightly different form than  otherwise available in
-PostgreSQL or TimescaleDB. They are re-implemented within the [two-step aggregates
+$PG or TimescaleDB. They are re-implemented within the [two-step aggregates
 framework](./two-step_aggregation.md) which exposes a summary form to the
 user which can then have multiple accessors.
 

_code-samples/toolkit/stats_agg-two-variables.md

@@ -19,7 +19,7 @@ For 1D statistical functions, see [Statistical Aggregates
 In order to make common statistical aggregates easier to work with in window
 functions and continuous aggregates, Toolkit provides common statistical
 aggregates in a slightly different form than  otherwise available in
-PostgreSQL or TimescaleDB. They are re-implemented within the [two-step aggregates
+$PG or TimescaleDB. They are re-implemented within the [two-step aggregates
 framework](./two-step_aggregation.md) which exposes a summary form to the user
 which can then have multiple accessors.
 

_code-samples/toolkit/two-step_aggregation.md

@@ -18,7 +18,7 @@ The inner aggregate call creates a machine-readable partial form that can be use
 While the one-step calling convention is easier for the simple case, it becomes much more difficult and hard to reason about for slightly more complex use-cases detailed in the next section. We wanted the calling convention to remain consistent and easy to reason about so you can take advantage of the same functions even as you start doing more complicated analyses.  This also to keeps the docs consistent and prevents adding special cases everywhere.
 
 ## Why We Use Two-Step Aggregates <a id="two-step-philosophy"></a>
-Interestingly, almost all Postgres aggregates do a version of this [under the hood already](https://www.postgresql.org/docs/current/xaggr.html), where they have an internal state used for aggregation and then a final function that displays the output to the user.
+Interestingly, almost all $PG aggregates do a version of this [under the hood already](https://www.postgresql.org/docs/current/xaggr.html), where they have an internal state used for aggregation and then a final function that displays the output to the user.
 
 So why do we make this calling convention explicit?
 

_partials/_add-data-twelvedata-crypto.md

@@ -12,9 +12,9 @@ download the dataset, then upload the data to your $SERVICE_LONG.
    This test dataset contains second-by-second trade data for the most-traded crypto-assets
    and a regular table of asset symbols and company names.  
 
-   To import up to 100GB of data directly from your current PostgreSQL based database, 
-   [migrate with downtime][migrate-with-downtime] using native PostgreSQL tooling. To seamlessly import 100GB-10TB+ 
-   of data, use the [live migration][migrate-live] tooling supplied by $COMPANY. To add data from non-PostgreSQL
+   To import up to 100GB of data directly from your current $PG-based database, 
+   [migrate with downtime][migrate-with-downtime] using native $PG tooling. To seamlessly import 100GB-10TB+ 
+   of data, use the [live migration][migrate-live] tooling supplied by $COMPANY. To add data from non-$PG
    data sources, see [Import and ingest data][data-ingest].