---
title: TimescaleDB Toolkit API reference | Tiger Data Docs
description: Analyze anything you have stored as time-series data, including IoT devices, IT systems, marketing analytics, user behavior, financial metrics, and cryptocurrency.
---

## [Approximate count distinct](/docs/reference/toolkit/approximate-count-distinct/index.md)

[Estimate the number of distinct values in a dataset, also known as cardinality estimation](/docs/reference/toolkit/approximate-count-distinct/index.md)

## [Statistical and regression analysis](/docs/reference/toolkit/statistical-and-regression-analysis/index.md)

[Functions for statistical analysis and linear regression on time-series data](/docs/reference/toolkit/statistical-and-regression-analysis/index.md)

## [Minimum and maximum](/docs/reference/toolkit/minimum-and-maximum/index.md)

[Find the smallest and largest values in a dataset](/docs/reference/toolkit/minimum-and-maximum/index.md)

## [Financial analysis](/docs/reference/toolkit/candlestick_agg/index.md)

[Perform analysis of financial asset data](/docs/reference/toolkit/candlestick_agg/index.md)

## [Percentile approximation](/docs/reference/toolkit/percentile-approximation/index.md)

[Estimate percentile values and percentile ranks using memory-efficient approximation algorithms](/docs/reference/toolkit/percentile-approximation/index.md)

## [Counters and gauges](/docs/reference/toolkit/counters-and-gauges/index.md)

[Functions for analyzing monotonic counters and gauge metrics](/docs/reference/toolkit/counters-and-gauges/index.md)

## [Time-weighted calculations](/docs/reference/toolkit/time_weight/index.md)

[Calculate time-weighted summary statistics for unevenly sampled data](/docs/reference/toolkit/time_weight/index.md)

## [Downsampling](/docs/reference/toolkit/downsampling/index.md)

[Functions for downsampling time-series data to visualize trends while preserving visual similarity](/docs/reference/toolkit/downsampling/index.md)

## [Timevector](/docs/reference/toolkit/timevector/index.md)

[Functions for working with time-series data as ordered sequences of time-value pairs](/docs/reference/toolkit/timevector/index.md)

## [Frequency analysis](/docs/reference/toolkit/frequency-analysis/index.md)

[Functions for analyzing the frequency of values in time-series data](/docs/reference/toolkit/frequency-analysis/index.md)

## [State tracking](/docs/reference/toolkit/state-tracking/index.md)

[Functions for tracking state transitions and system liveness over time](/docs/reference/toolkit/state-tracking/index.md)

## [Saturating math](/docs/reference/toolkit/saturating-math/index.md)

[Perform saturating math operations on integers](/docs/reference/toolkit/saturating-math/index.md)

TimescaleDB Toolkit extends TimescaleDB with additional hyperfunctions for advanced time-series analysis. For hyperfunctions included by default in TimescaleDB, see the [TimescaleDB hyperfunctions documentation](/docs/reference/timescaledb/hyperfunctions/index.md).