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Copy file name to clipboardExpand all lines: CONTRIBUTING.md
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# Contribute to TigerData documentation
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# Contribute to Tiger Data documentation
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TigerData documentation is open for contribution from all community members. The current source is in this repository.
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Tiger Data documentation is open for contribution from all community members. The current source is in this repository.
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This page explains the structure and language guidelines for contributing to TigerData documentation. See the [README][readme] for how to contribute.
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This page explains the structure and language guidelines for contributing to Tiger Data documentation. See the [README][readme] for how to contribute.
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## Language
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Write in a clear, concise, and actionable manner. TigerData documentation uses the [Google Developer Documentation Style Guide][google-style] with the following exceptions:
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Write in a clear, concise, and actionable manner. Tiger Data documentation uses the [Google Developer Documentation Style Guide][google-style] with the following exceptions:
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- Do not capitalize the first word after a colon.
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- Use code font (back ticks) for UI elements instead of semi-bold.
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## Formatting
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In addition to all the [regular Markdown formatting][markdown-syntax], the following elements are available for TigerData docs:
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In addition to all the [regular Markdown formatting][markdown-syntax], the following elements are available for Tiger Data docs:
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- Procedure blocks
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- Highlight blocks
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## Variables
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TigerData documentation uses variables for its product names, features, and UI elements in Tiger Cloud Console with the following syntax: `$VARIABLE_NAME`. Variables do not work inside the following:
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Tiger Data documentation uses variables for its product names, features, and UI elements in Tiger Cloud Console with the following syntax: `$VARIABLE_NAME`. Variables do not work inside the following:
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- Front matter on each page
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- HTML tables and tabs
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- 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:
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- Title: Create a hypertable in Tiger Cloud
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- Description: Turn a regular $PG table into a hypertable in a few steps, using Tiger Cloud Console.
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- Description: Turn a regular Postgres table into a hypertable in a few steps, using Tiger Cloud Console.
[](https://console.cloud.timescale.com/signup)
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[](https://console.cloud.timescale.com/signup)
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</div>
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This repository contains the current source for TigerData documentation available at https://docs.tigerdata.com/.
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This repository contains the current source for Tiger Data documentation available at https://docs.tigerdata.com/.
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We welcome contributions! You can contribute to TigerData documentation in the following ways:
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We welcome contributions! You can contribute to Tiger Data documentation in the following ways:
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-[Create an issue][docs-issues] in this repository and describe the proposed change. Our doc team takes care of it.
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- Update the docs yourself and have your change reviewed and published by our doc team.
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## Contribute to the TigerData docs
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## Contribute to the Tiger Data docs
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To make the contribution yourself:
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See the [Contributing guide](CONTRIBUTING.md) for style and language guidance.
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## Learn about TigerData
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## Learn about Tiger Data
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TigerData is Postgres made powerful. To learn more about the company and its products, visit [tigerdata.com](https://www.tigerdata.com).
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Tiger Data is Postgres made powerful. To learn more about the company and its products, visit [tigerdata.com](https://www.tigerdata.com).
You are charged for all active $SERVICE_SHORTs in your account, even if you are not actively using them. To reduce costs, pause or delete your unused $SERVICE_SHORTs.
Copy file name to clipboardExpand all lines: _partials/_caggs-intro.md
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import RealTimeAgg from 'versionContent/_partials/_real-time-aggregates.mdx';
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In modern applications, data usually grows very quickly. This means that aggregating
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it into useful summaries can become very slow. Continuous aggregates in $TIMESCALE_DB make
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aggregating data lightning fast, accurate, and easy.
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If you are collecting data very frequently, you might want to aggregate your
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data into minutes or hours instead. For example, if an IoT device takes
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it into useful summaries can become very slow. If you are collecting data very frequently, you might want to aggregate your
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data into minutes or hours instead. For example, if an IoT device takes
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temperature readings every second, you might want to find the average temperature
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for each hour. Every time you run this query, the database needs to scan the
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entire table and recalculate the average.
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entire table and recalculate the average. $TIMESCALE_DB makes aggregating data lightning fast, accurate, and easy with continuous aggregates.
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Continuous aggregates are a kind of hypertable that is refreshed automatically
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Continuous aggregates in $TIMESCALE_DB are a kind of hypertable that is refreshed automatically
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in the background as new data is added, or old data is modified. Changes to your
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dataset are tracked, and the hypertable behind the continuous aggregate is
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automatically updated in the background.
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You don't need to manually refresh your continuous aggregates, they are
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continuously and incrementally updated in the background. Continuous aggregates
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also have a much lower maintenance burden than regular $PG materialized
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Continuous aggregates have a much lower maintenance burden than regular $PG materialized
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views, because the whole view is not created from scratch on each refresh. This
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means that you can get on with working your data instead of maintaining your
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database.
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Because continuous aggregates are based on hypertables, you can query them in exactly the same way as your other tables. This includes continuous aggregates in the rowstore, compressed into the [columnstore][hypercore],
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or [tiered to object storage][data-tiering]. You can even create [continuous aggregates on top of your continuous aggregates][hierarchical-caggs] - for an even more fine-tuned aggregation.
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or [tiered to object storage][data-tiering]. You can even create [continuous aggregates on top of your continuous aggregates][hierarchical-caggs], for an even more fine-tuned aggregation.
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[Real-time aggregation][real-time-aggregation] enables you to combine pre-aggregated data from the materialized view with the most recent raw data. This gives you up-to-date results on every query. <RealTimeAgg />
import CreateAccountConsole from "versionContent/_partials/_create-account-console.mdx";
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You create a $ACCOUNT_LONG to manage your $SERVICE_SHORTs and data in a centralized and efficient manner in $CONSOLE. From there, you can create and delete $SERVICE_SHORTs, run queries, manage access and billing, integrate other services, contact support, and more.
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