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# Tiger Data Documentation llms.txt

docs.timescale.com/llms.txt

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llms.txt

Docs

Build with Tiger Data

Set up hypercore

Convert continuous aggregates to the columnstore

Create a continuous aggregate

Create an index on a continuous aggregate

Drop data from continuous aggregates

Migrate a continuous aggregate to the new form

Refresh continuous aggregates

Cost optimization

Write and query data

About automation

Create and manage custom jobs

Add a data retention policy

Create a custom job to downsample and compress chunks

Create a custom retention job

Create a custom job for automatic tablespace management

Hyperfunctions overview

Counter aggregation

Function pipelines

Overview

Last observation carried forward

Time bucket gapfill

Heartbeat aggregation

Approximate count distincts with Hyperloglog

Overview

Percentile approximation advanced aggregation methods

Approximate percentiles

Statistical aggregation

Time-weighted averages and integrals

Perform advanced analytic queries

SELECT data

Run your queries from Tiger Console

Manage storage and tiering

Query tiered data

Replicas and forks with tiered data

Delete data

Insert data

Update data

Upsert data

Tutorials

Aggregate organizational data with AI agents

Analyze Bitcoin blockchain

Analyze energy consumption

Analyze application events with UUIDv7

Visualize financial tick data with Grafana

Analyze NYC taxi data

Analyze stock market data

Visualize transport and geospatial data with Grafana

Tiger Data cookbook

Create Tiger Cloud services with the Terraform provider

Build hybrid search with BM25 and vector similarity

Ingest real-time financial data

Simulate an IoT sensor dataset

Quickstarts

Basic compression with hypercore

Your first hypertable

Performance optimization

Alter and update table schemas

Automate tasks with triggers

Automatically route queries to continuous aggregates

Ensure data integrity with constraints

Handle semi-structured data with JSON

Enforce constraints with unique indexes

Improve hypertable and query performance

Accelerate queries using indexes

Improve storage performance using tablespaces

Query external data sources with FDW

Retrofit chunk intervals on a production hypertable

Improve query and upsert performance

Get faster DISTINCT queries with SkipScan

Troubleshooting

Troubleshoot continuous aggregates

Troubleshoot data retention

Troubleshoot data tiering

Troubleshoot hypercore

Troubleshoot hyperfunctions

Troubleshoot hypertables

Troubleshoot import and ingest

Troubleshoot jobs

Troubleshoot queries

Troubleshoot schema management

Troubleshoot time buckets

Deploy Tiger Data products

Tiger Cloud

Limitations

Managed Service for TimescaleDB

About MST

Aiven Client

Billing

Connection pools

Create an MST service

Use the Postgres dblink extension

Supported extensions

Failover

Identify and repair issues with PostgreSQL indexes with REINDEX

Ingest data

Integrations

Visualize data with Google Data Studio

Visualize data with Grafana

Logging

Send metrics to Datadog

Set up a Prometheus endpoint

Maintenance

Backups

Migrate data from self-hosted TimescaleDB to MST

Create a read-only replica

REST API

Security

Troubleshooting

User management

Viewing service logs

VPC peering

Configure VPC peering

VPC peering on AWS

AWS Transit Gateway

VPC peering on Azure

VPC peering on GCP

Self-hosted TimescaleDB

Backup and restore

Logical backup with pg_dump and pg_restore

Physical backups

Configuration

About configuration in TimescaleDB

Configuration with Docker

Manual PostgreSQL configuration and tuning

Telemetry and version checking

TimescaleDB configuration and tuning

TimescaleDB tuning tool

Manage storage using tablespaces

Migrate your PostgreSQL database to self-hosted TimescaleDB

Migrate the entire database at once

Migrate data to TimescaleDB from InfluxDB

Migrate data to TimescaleDB from the same PostgreSQL instance

Migrate schema and data separately

Replication and high availability

About high availability

Configure replication

Additional tooling

About timescaledb-tune

Install, update, and uninstall TimescaleDB Toolkit

Troubleshooting

Uninstall TimescaleDB

Upgrade TimescaleDB

Downgrade to a previous version of TimescaleDB

Major TimescaleDB upgrades

Minor TimescaleDB upgrades

Upgrade TimescaleDB running in Docker

Upgrade PostgreSQL

About configuration in Tiger Cloud

Advanced parameters

Configure database parameters

Back up and recover services

Manage high availability

Overview

Read scaling

Monitor your services

Billing and account management

Private endpoints

Client credentials

IP allow list

Control user access to projects

Multi-factor authentication

About security in Tiger Cloud

Manage data security in your service

SAML authentication

Connect with a stricter SSL mode

AWS Transit Gateway

VPC Peering

About Tiger Cloud services

Manually change compute resources

Connection pooling

Fork services

Service explorer

Service management

Tiger Console overview

PostgreSQL extensions

Optimize full text search with BM25

Encrypt data using pgcrypto

Create a chatbot using pgvector

Analyse geospatial data with PostGIS

Maintenance and upgrades

About configuration in Tiger Cloud

Advanced parameters

Configure database parameters

Back up and recover services

Manage high availability

Overview

Read scaling

Monitor your services

Billing and account management

Private endpoints

Client credentials

IP allow list

Control user access to projects

Multi-factor authentication

About security in Tiger Cloud

Manage data security in your service

SAML authentication

Connect with a stricter SSL mode

About Tiger Cloud services

Manually change compute resources

Connection pooling

Fork services

Service explorer

Service management

Tiger Console overview

PostgreSQL extensions

Optimize full text search with BM25

Encrypt data using pgcrypto

Create a chatbot using pgvector

Analyse geospatial data with PostGIS

Maintenance and upgrades

Troubleshoot Tiger Cloud

Vectorizer and in-database LLM calls migration guide

Get started with Tiger Data

Install self-hosted TimescaleDB

Supported platforms

Compare TimescaleDB editions

Cloud-exclusive features

Contribute to the docs

Feature comparison

News and updates

Changelog

Release notes

Connect your app

Create a Tiger Cloud service

Integrate Tiger Cloud with your AI Agent (MCP and CLI)

5-minute quickstart

Get started with the REST API

Get started with Tiger CLI

10-minute quickstart

Tiger Data Documentation

Integrate with Tiger Data

BI & visualization

Integrate Power BI with Tiger Cloud

Integrate Tableau and Tiger Cloud

Code and libraries

Connect your app

Configuration & deployment

Integrate TimescaleDB with CloudNativePG on Kubernetes

Integrate Kubernetes with Tiger Cloud

Integrate Terraform with Tiger Cloud

Connectors

Query TigerLake S3 Tables with AWS Glue and Athena

Query TigerLake S3 Tables from Snowflake

Integrate data lakes with Tiger Cloud

Stream data from Kafka

Sync data from Postgres

Sync data from S3

Data engineering & ETL

Integrate Amazon SageMaker with Tiger Cloud

Integrate Apache Airflow with Tiger Cloud

Integrate AWS Lambda with Tiger Cloud

Integrate Debezium with TimescaleDB

Integrate Decodable with Tiger Cloud

Integrate Supabase with Tiger Cloud

Data ingestion & streaming

Integrate Apache Kafka with Tiger Cloud

Integrate EMQX with Tiger Cloud

Integrate Fivetran with Tiger Cloud

Integrate HighByte with Tiger Cloud

Integrate HiveMQ with Tiger Cloud

Integrate Ignition with Tiger Cloud

Integrate Kepware KEPServerEX with Tiger Cloud

Integrate Litmus Edge with Tiger Cloud

Integrate Node-RED with Tiger Cloud

Connect to Tiger Data

Observability & alerting

Integrate Azure Monitor with Tiger Cloud

Integrate Amazon CloudWatch with Tiger Cloud

Integrate Datadog with Tiger Cloud

Metrics exported by Tiger Cloud exporters

Integrate Grafana with Tiger Cloud

Integrate Prometheus with Tiger Cloud

Integrate Telegraf with Tiger Cloud

Query & administration

Integrate Azure Data Studio with Tiger Cloud

Integrate DBeaver with Tiger Cloud

Integrate pgAdmin with Tiger Cloud

Integrate Postgres with Tiger Cloud

Connect to Tiger Cloud with psql

Integrate qStudio with Tiger Cloud

Secure connectivity

Integrate Amazon Web Services with Tiger Cloud

Integrate your data center with Tiger Cloud

Integrate Google Cloud with Tiger Cloud

Integrate Microsoft Azure with Tiger Cloud

Troubleshoot

Integrate

Component kitchen sink

Get to know Tiger Data

Feature comparison

Understand capabilities

Understand chunks

Compression methods in hypercore

Understand hypercore

Understand continuous aggregates

Hierarchical continuous aggregates

Materialized hypertables

Real-time aggregates

Time and continuous aggregates

Understand the data lifecycle

Understand data retention

About data retention with continuous aggregates

Manually drop chunks

Understand tiered storage

Understand time buckets

Use time buckets

Understand the data lifecycle

Design your data model

Primary keys, time columns, and uniqueness for hypertables

Understand schema optimization

Wide, narrow, and medium tables

Deep dive overview

Tiger Data architecture for real-time analytics

Glossary

About TimescaleDB hyperfunctions

Create and configure a hypertable

Hypertable indexes

Hypertable operations

Partition a hypertable

Size hypertable chunks

Understand hypertables

Key vector concepts for pgvector

Understand pgvector and pgvectorscale

Understand pg_textsearch and BM25 search

Tiger Cloud

Cloud-exclusive features

Supported regions

Tiger Cloud essentials

Data

Migrate to Tiger Cloud

Choose a migration approach

Dual-write and backfill

Migrate from non-PostgreSQL using dual-write and backfill

Migrate from PostgreSQL using dual-write and backfill

Migrate from TimescaleDB using dual-write and backfill

Migrate with timescaledb-backfill

Upload a file using Tiger Console

Upload a file using the terminal

Live migration (deprecated)

Stream data from Kafka

Sync data from PostgreSQL

Sync data from S3

Livesync replication

Livesync replication advanced topics

Livesync replication troubleshooting

Migrate with downtime

FAQ and troubleshooting

Reference

Configuration reference

Tiger Cloud API reference

Tiger Cloud REST API (local preview)

Data tiering overview

add_tiering_policy()

disable_tiering()

remove_tiering_policy()

tier_chunk()

untier_chunk()

Tiger CLI reference

Tiger MCP reference

TimescaleDB API reference

Administrative functions

get_telemetry_report()

timescaledb_post_restore()

timescaledb_pre_restore()

Service configuration

Grand Unified Configuration (GUC) parameters

Configuration parameters

Continuous aggregates overview

add_continuous_aggregate_policy()

add_policies()

ALTER MATERIALIZED VIEW (continuous aggregate)

alter_policies()

cagg_migrate()

CREATE MATERIALIZED VIEW (continuous aggregate)

DROP MATERIALIZED VIEW (continuous aggregate)

refresh_continuous_aggregate()

remove_all_policies()

remove_continuous_aggregate_policy()

remove_policies()

show_policies()

Data retention overview

add_retention_policy()

remove_retention_policy()

Hypercore

add_columnstore_policy()

ALTER TABLE (hypercore)

timescaledb_information.chunk_columnstore_settings

chunk_columnstore_stats()

convert_to_columnstore()

convert_to_rowstore()

timescaledb_information.hypertable_columnstore_settings

hypertable_columnstore_stats()

remove_columnstore_policy()

Hyperfunctions overview

Distribution analysis overview

approximate_row_count()

histogram()

Gapfilling overview

interpolate()

locf()

time_bucket_gapfill()

Time series utilities overview

days_in_month()

first()

last()

month_normalize()

time_bucket()

to_epoch()

Hypertables and chunks

add_dimension()

add_dimension() (deprecated)

add_reorder_policy()

attach_chunk()

attach_tablespace()

chunk_rewrite_cleanup()

chunks_detailed_size()

create_chunk()

create_hypertable()

create_hypertable() (old interface)

CREATE INDEX (transaction per chunk)

CREATE TABLE

detach_chunk()

detach_tablespace()

detach_tablespaces()

disable_chunk_skipping()

drop_chunk()

drop_chunks()

enable_chunk_skipping()

hypertable_approximate_detailed_size()

hypertable_approximate_size()

hypertable_detailed_size()

hypertable_index_size()

hypertable_size()

merge_chunks()

merge_chunks_concurrently()

move_chunk()

remove_reorder_policy()

reorder_chunk()

set_chunk_time_interval()

set_integer_now_func()

show_chunks()

show_tablespaces()

split_chunk()

Informational views overview

timescaledb_information.chunk_columnstore_settings

timescaledb_information.chunks

timescaledb_information.continuous_aggregates

timescaledb_information.dimensions

timescaledb_information.hypertable_columnstore_settings

timescaledb_information.hypertables

timescaledb_information.job_errors

timescaledb_information.job_history

timescaledb_information.job_stats

timescaledb_information.jobs

timescaledb_experimental.policies

Jobs and automation overview

add_job()

alter_job()

delete_job()

run_job()

API reference tag overview

UUIDv7 functions

generate_uuidv7()

to_uuidv7()

to_uuidv7_boundary()

uuid_timestamp()

uuid_timestamp_micros()

uuid_version()

TimescaleDB Toolkit API reference

Approximate count distinct overview

approx_count_distinct()

distinct_count()

hyperloglog()

rollup()

stderror()

Financial analysis overview

candlestick()

candlestick_agg()

close()

close_time()

high()

high_time()

low()

low_time()

open()

open_time()

rollup()

volume()

vwap()

Counters and gauges overview

Counter aggregation overview

corr()

counter_agg()

counter_zero_time()

delta()

extrapolated_delta()

extrapolated_rate()

first_time()

first_val()

idelta_left()

idelta_right()

intercept()

interpolated_delta()

interpolated_rate()

irate_left()

irate_right()

last_time()

last_val()

num_changes()

num_elements()

num_resets()

rate()

rollup()

slope()

time_delta()

with_bounds()

Gauge aggregation overview

corr()

delta()

extrapolated_delta()

extrapolated_rate()

gauge_agg()

gauge_zero_time()

idelta_left()

idelta_right()

intercept()

interpolated_delta()

interpolated_rate()

irate_left()

irate_right()

num_changes()

num_elements()

rate()

rollup()

slope()

time_delta()

with_bounds()

Downsampling overview

asap_smooth()

gp_lttb()

lttb()

Frequency analysis overview

Count-min sketch overview

approx_count()

count_min_sketch()

Frequency aggregation overview

freq_agg()

into_values()

max_frequency()

mcv_agg()

min_frequency()

rollup()

topn()

Minimum and maximum overview

Maximum values overview

Maximum values by overview

into_values()

max_n_by()

rollup()

into_array()

into_values()

max_n()

rollup()

Minimum values overview

Minimum values by overview

into_values()

min_n_by()

rollup()

into_array()

into_values()

min_n()

rollup()

Percentile approximation overview

t-digest overview

approx_percentile()

approx_percentile_rank()

max_val()

mean()

min_val()

num_vals()

rollup()

tdigest()

total()

UddSketch overview

approx_percentile()

approx_percentile_array()

approx_percentile_rank()

error()

mean()

num_vals()

percentile_agg()

rollup()

total()

uddsketch()

Saturating math overview

saturating_add()

saturating_add_pos()

saturating_mul()

saturating_sub()

saturating_sub_pos()

State tracking overview

Compact state aggregation overview

compact_state_agg()

duration_in()

interpolated_duration_in()

into_values()

rollup()

Heartbeat aggregation overview

dead_ranges()

downtime()

heartbeat_agg()

interpolate()

interpolated_downtime()

interpolated_uptime()

live_at()

live_ranges()

num_gaps()

num_live_ranges()

rollup()

trim_to()

uptime()

State aggregation overview

duration_in()

interpolated_duration_in()

interpolated_state_periods()

interpolated_state_timeline()

into_values()

rollup()

state_agg()

state_at()

state_periods()

state_timeline()

Statistical and regression analysis overview

stats_agg (one variable) overview

average()

kurtosis()

num_vals()

rolling()

rollup()

skewness()

stats_agg() (one variable)

stddev()

sum()

variance()

stats_agg (two variables) overview

average_y() | average_x()

corr()

covariance()

determination_coeff()

intercept()

kurtosis_y() | kurtosis_x()

num_vals()

rolling()

rollup()

skewness_y() | skewness_x()

slope()

stats_agg() (two variables)

stddev_y() | stddev_x()

sum_y() | sum_x()

variance_y() | variance_x()

x_intercept()

Time-weighted calculations overview

average()

first_time()

first_val()

integral()

interpolated_average()

interpolated_integral()

last_time()

last_val()

rollup()

time_weight()

Timevector overview

rollup()

timevector()

unnest()

Learn

API Reference

Retrieve Info

## What is Tiger Data Documentation's llms.txt?

Tiger Data Documentation publishes an `/llms.txt` file that provides AI systems with a structured index of its documentation. It follows the [llms.txt specification](https://llmstxt.org), organizing links to guides, API references, and tutorials under section headings so that LLMs like ChatGPT, Claude, and Gemini can quickly understand what Tiger Data Documentation offers and where to find details.

Issues

Spec

2

Sections

680

Links

119.1 KB

Size

~30.5k

Tokens

Sections: Docs · API Reference

## Add Tiger Data Documentation Docs to Your AI Assistant

Select your tool to see how to add Tiger Data Documentation's llms.txt as a documentation source.

Cursor

 Windsurf

 Claude Code

 ChatGPT

 Zed

 Copilot

1. 1

   Open any chat or composer panel
2. 2

   Type @Docs and select "Add new doc"
3. 3

   Paste the URL: https://docs.timescale.com/llms.txt
4. 4

   Wait for the green dot (indexing complete)
5. 5

   Reference @Docs in chat when asking about Tiger Data Documentation

Cursor crawls the URL and indexes all subpages. Add a trailing slash to index child pages too.

## Spec Compliance 2 errors

## Frequently Asked Questions

Where is Tiger Data Documentation's llms.txt file?

Tiger Data Documentation publishes its llms.txt at https://docs.timescale.com/llms.txt. This file provides a structured, markdown-formatted index of Tiger Data Documentation's documentation that AI systems can consume to understand the project's APIs, guides, and references.

How do I use Tiger Data Documentation's llms.txt with AI coding assistants?

Copy the llms.txt content and paste it into your AI assistant (Cursor, Windsurf, Claude, ChatGPT) as context. This gives the AI an accurate map of Tiger Data Documentation's documentation so it can provide better code suggestions and answers about Tiger Data Documentation.

What does Tiger Data Documentation's llms.txt contain?

Tiger Data Documentation's llms.txt contains 2 sections and 680 documentation links in 119.1 KB (~30.5k tokens). Key sections include Docs, API Reference.

How many tokens does Tiger Data Documentation's llms.txt use?

The concise llms.txt index is approximately 30.5k tokens (119.1 KB). Most AI assistants can fit this within their context window. For the full expanded documentation, look for an llms-full.txt variant which embeds all content inline.

Can I generate an llms.txt for my own project?

Yes. Use the free llms.txt generator at mdream.dev/tools/llms-txt/generator to crawl your site and produce a spec-compliant llms.txt file. You can also validate existing files with the llms.txt validator.

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