timescale · billy-the-fish · Mar 10, 2025 · Feb 10, 2025 · Feb 10, 2025 · Feb 10, 2025
diff --git a/.github/styles/Vocab/Timescale/accept.txt b/.github/styles/Vocab/Timescale/accept.txt
@@ -2,6 +2,7 @@
 Aiven
 Alertmanager
 API
+api
 Anthropic
 async
 [Aa]utoscal(?:e|ing)
@@ -16,6 +17,7 @@ https?
 BSD
 [Cc]allouts?
 COPY
+[Cc]opy
 [Cc]lickstreams?
 Cloudformation
 Cloudwatch

diff --git a/.github/styles/config/vocabularies/Timescale/accept.txt b/.github/styles/config/vocabularies/Timescale/accept.txt
@@ -0,0 +1,159 @@
+[Aa]ccessor
+Aiven
+Alertmanager
+API
+api
+Anthropic
+async
+[Aa]utoscal(?:e|ing)
+[Bb]ackfill(?:ing)?
+cron
+csv
+https?
+(?i)bigint
+[Bb]itemporal
+[Bb]lockchains?
+[Bb]oolean
+BSD
+[Cc]allouts?
+COPY
+[Cc]opy
+[Cc]lickstreams?
+Cloudformation
+Cloudwatch
+config
+[Cc]onstif(?:y|ied)
+[Cc]rypto
+[Cc]ryptocurrenc(?:y|ies)
+Datadog
+[Dd]efragment(:?s|ed)?
+Django
+distincts
+Docker
+[Dd]ownsampl(?:e|ing)
+erroring
+Ethereum
+[Ff]ailover
+[Ff]inalizers?
+[Ff]orex
+[Gg]apfill(?:ing)?
+[Gg]eospatial
+GitHub
+GNU
+Grafana
+GUC
+gsed
+gzip(?:ped)?
+Hasura
+HipChat
+[Hh]ostname
+href
+[Hh]yperloglog
+[Hh]yperfunctions?
+[Hh]ypertables?
+[Hh]ypershift
+img
+Indri
+[Ii]nserter
+[Ii]ntraday
+[Iin]validation
+ivfflat
+jpg
+JDBC
+JDK
+JSON
+Kafka
+Kaggle
+Kinesis
+[Ll]ambda
+LangChain
+LlamaIndex
+LLMs
+[Ll]ookups?
+loopback
+[Mm]atchers?
+[Mm]aterializer
+(?i)MST
+matplotlib
+[Mm]utators?
+Nagios
+[Nn]amespaces?
+[Nn]ullable
+Outflux
+[Pp]ageviews?
+[Pp]aralleliza(?:ble|tion)
+[Pp]athname
+Patroni
+Paulo
+[Pp]erformant
+pg_dump
+pg_restore
+[Pp]gvector
+[Pp]laintext
+Plotly
+pre
+POSIX
+PostgreSQL
+[Pp]ooler?
+Prometheus
+PromLens
+PromQL
+Promscale
+Protobuf
+psql
+[Qq]uantiles?
+qStudio
+RDS
+[Rr]edistribut(?:e|able)
+[Rr]eindex(?:ed)?
+reltuples
+[Rr]eusability
+[Rr]unbooks?
+[Ss]crollable
+Sequelize
+[Ss]ignups?
+[Ss]iloed
+(?i)smallint
+sed
+src
+[Ss]ubquer(?:y|ies)
+[Ss]ubsets?
+[Ss]upersets?
+[Tt]ablespaces?
+Telegraf
+Thanos
+Threema
+[Tt]iering
+[Tt]imevectors?
+Timescale(?:DB)?
+tobs
+[Tt]ransactionally
+tsdbadmin
+Uber
+[Uu]nary
+[Uu]ncomment
+[Uu]nencrypted
+Unix
+[Uu]nmaterialized
+[Uu]nregister
+[Uu]nthrottled?
+[Uu]ntier
+[Uu]pserts?
+[Rr]ebalanc(?:e|ing)
+[Rr]epos?
+[Rr]ollups?
+[Ss]erverless
+[Ss]hard(?:s|ing)?
+SkipScan
+(?i)timestamptz
+URLs?
+URIs?
+UUID
+versionContent
+[Vv]irtualenv
+WAL
+[Ww]ebsockets?
+Worldmap
+www
+Zabbix
+Zipkin
diff --git a/_partials/_add-data-blockchain.md b/_partials/_add-data-blockchain.md
@@ -1,16 +1,14 @@
 ## Load financial data
 
-This tutorial uses Bitcoin transactions from the past five days.
-
-## Ingest the dataset
+The dataset contains around 1.5 million Bitcoin transactions, the trades for five days. It includes
+information about each transaction, along with the value in [satoshi][satoshi-def]. It also states if a
+trade is a [coinbase][coinbase-def] transaction, and the reward a coin miner receives for mining the coin.
 
 To ingest data into the tables that you created, you need to download the
 dataset and copy the data to your database.
 
 <Procedure>
 
-### Ingesting the dataset
-
 1.  Download the `bitcoin_sample.zip` file. The file contains a `.csv`
     file that contains Bitcoin transactions for the past five days. Download:
 
@@ -37,3 +35,6 @@ dataset and copy the data to your database.
     resources.
 
 </Procedure>
+
+[satoshi-def]: https://www.pcmag.com/encyclopedia/term/satoshi
+[coinbase-def]: https://www.pcmag.com/encyclopedia/term/coinbase-transaction
diff --git a/_partials/_add-data-energy.md b/_partials/_add-data-energy.md
@@ -5,8 +5,6 @@ into the `metrics` hypertable.
 
 <Procedure>
 
-### Loading energy consumption  data
-
 <Highlight type="important">
 This is a large dataset, so it might take a long time, depending on your network
 connection.

diff --git a/_partials/_add-data-nyctaxis.md b/_partials/_add-data-nyctaxis.md
@@ -5,8 +5,6 @@ When you have your database set up, you can load the taxi trip data into the
 
 <Procedure>
 
-### Loading trip data
-
 <Highlight type="important">
 This is a large dataset, so it might take a long time, depending on your network
 connection.

diff --git a/_partials/_add-data-twelvedata-crypto.md b/_partials/_add-data-twelvedata-crypto.md
@@ -1,29 +1,29 @@
 ## Load financial data
 
 This tutorial uses real-time cryptocurrency data, also known as tick data, from
-[Twelve Data][twelve-data]. A direct download link is provided below.
+[Twelve Data][twelve-data]. To ingest data into the tables that you created, you need to 
+download the dataset, then upload the data to your $SERVICE_LONG.
 
-### Ingest the dataset
+<Procedure>
 
-To ingest data into the tables that you created, you need to download the
-dataset and copy the data to your database.
 
-<Procedure>
+1. Unzip <Tag type="download">[crypto_sample.zip](https://assets.timescale.com/docs/downloads/candlestick/crypto_sample.zip)</Tag> to a `<local folder>`.
 
-#### Ingesting the dataset
+   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.  
 
-1.  Download the `crypto_sample.zip` file. The file contains two `.csv`
-    files; one with company information, and one with real-time stock trades for
-    the past month. Download:
-    <Tag
-    type="download">[crypto_sample.zip](https://assets.timescale.com/docs/downloads/candlestick/crypto_sample.zip)
-    </Tag>
+   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
+   data sources, see [Import and ingest data][data-ingest].
 
-1.  In a new terminal window, run this command to unzip the `.csv` files:
 
-    ```bash
-    unzip crypto_sample.zip
-    ```
+
+1. In Terminal, navigate to `<local folder>` and connect to your $SERVICE_SHORT.
+   ```bash
+   psql -d "postgres://<username>:<password>@<host>:<port>/<database-name>"
+   ```
+   The connection information for a $SERVICE_SHORT is available in the file you downloaded when you created it.
 
 1.  At the `psql` prompt, use the `COPY` command to transfer data into your
     Timescale instance. If the `.csv` files aren't in your current directory,
@@ -44,3 +44,6 @@ dataset and copy the data to your database.
 </Procedure>
 
 [twelve-data]: https://twelvedata.com/
+[migrate-with-downtime]: /migrate/:currentVersion:/pg-dump-and-restore/
+[migrate-live]: /migrate/:currentVersion:/live-migration/
+[data-ingest]: /use-timescale/:currentVersion:/ingest-data/
diff --git a/_partials/_add-data-twelvedata-stocks.md b/_partials/_add-data-twelvedata-stocks.md
@@ -3,15 +3,11 @@
 This tutorial uses real-time stock trade data, also known as tick data, from
 [Twelve Data][twelve-data]. A direct download link is provided below.
 
-## Ingest the dataset
-
 To ingest data into the tables that you created, you need to download the
 dataset and copy the data to your database.
 
 <Procedure>
 
-#### Ingesting the dataset
-
 1.  Download the `real_time_stock_data.zip` file. The file contains two `.csv`
     files; one with company information, and one with real-time stock trades for
     the past month. Download:

diff --git a/_partials/_caggs-intro.md b/_partials/_caggs-intro.md
@@ -1,12 +1,12 @@
-Time-series data usually grows very quickly. And that means that aggregating the
-data into useful summaries can become very slow. Continuous aggregates makes
-aggregating data lightning fast.
+In modern applications, data usually grows very quickly. This means that aggregating 
+it into useful summaries can become very slow. $CLOUD_LONG continuous aggregates make
+aggregating data lightning fast, accurate, and easy. 
 
 If you are collecting data very frequently, you might want to aggregate your
-data into minutes or hours instead. For example, if you have a table of
-temperature readings taken every second, you can find the average temperature
+data into minutes or hours instead. For example, if an IoT device takes 
+temperature readings every second, you might want to find the average temperature
 for each hour. Every time you run this query, the database needs to scan the
-entire table and recalculate the average every time.
+entire table and recalculate the average.
 
 Continuous aggregates are a kind of hypertable that is refreshed automatically
 in the background as new data is added, or old data is modified. Changes to your
@@ -21,10 +21,10 @@ means that you can get on with working your data instead of maintaining your
 database.
 
 Because continuous aggregates are based on hypertables, you can query them in
-exactly the same way as your other tables, and enable [Hypercore][hypercore]
-or [tiered storage][data-tiering] on your continuous aggregates. You can even
+exactly the same way as your other tables, and enable [compression][compression]
+or [tiered storage][data-tiering] on them. You can even
 create
-[continuous aggregates on top of your continuous aggregates][hierarchical-caggs].
+[continuous aggregates on top of your continuous aggregates][hierarchical-caggs] - for an even more fine-tuned aggregation. 
 
 By default, querying continuous aggregates provides you with real-time data.
 Pre-aggregated data from the materialized view is combined with recent data that

diff --git a/_partials/_cloud-create-connect-tutorials.md b/_partials/_cloud-create-connect-tutorials.md
@@ -6,9 +6,7 @@ command-line utility. If you've used PostgreSQL before, you might already have
 
 <Procedure>
 
-### Create a Timescale service and connect to the service
-
-1.  In the [Timescale portal][timescale-portal], click `Create service`.
+1.  In the [$CONSOLE][timescale-portal], click `Create service`.
 1.  Click `Download the cheatsheet` to download an SQL file that contains the
     login details for your new service. You can also copy the details directly
     from this page. When you have copied your password,

diff --git a/_partials/_create-hypertable-blockchain.md b/_partials/_create-hypertable-blockchain.md
@@ -1,5 +1,5 @@
 
-## Create a hypertable
+## Optimize time-series data in hypertables
 
 Hypertables are the core of Timescale. Hypertables enable Timescale to work
 efficiently with time-series data. Because Timescale is PostgreSQL, all the
@@ -9,8 +9,6 @@ with Timescale tables similar to standard PostgreSQL.
 
 <Procedure>
 
-### Creating a hypertable
-
 1.  Create a standard PostgreSQL table to store the Bitcoin blockchain data
     using `CREATE TABLE`:
 

diff --git a/_partials/_create-hypertable-energy.md b/_partials/_create-hypertable-energy.md
@@ -1,4 +1,4 @@
-## Create a hypertable
+## Optimize time-series data in hypertables
 
 Hypertables are the core of Timescale. Hypertables enable Timescale to work
 efficiently with time-series data. Because Timescale is PostgreSQL, all the
@@ -8,8 +8,6 @@ with Timescale tables similar to standard PostgreSQL.
 
 <Procedure>
 
-### Creating a hypertable
-
 1.  Create a standard PostgreSQL table to store the energy consumption data
     using `CREATE TABLE`: