---
title: What is a Hypertable? | Tiger Data Docs
description: Learn how hypertables partition time-series data automatically
---

**Tiger Data 101** → TimescaleDB | **Section:** Hypertables | **⏱ Time:** \~3 min

## Learning objectives

By the end of this module, you will be able to:

- **Define** hypertables and **explain** their role in TimescaleDB architecture (Understand)
- **Demonstrate** how to create and configure hypertables for time-series data (Apply)
- **Apply** partitioning strategies to hypertables for optimal performance (Apply)
- **Analyze** hypertable indexing and optimization techniques and **implement** improvements (Analyze/Apply)

---

## What is a hypertable?

A **hypertable** is a virtual table abstraction that wraps a time-series table and automatically partitions it into smaller, manageable pieces called **chunks**. From your application's perspective, you query it just like a regular table.

Under the hood, TimescaleDB handles all the complexity:

- **Automatic time-based partitioning**: Data is split into chunks, typically one per time interval (e.g., one chunk per day)
- **Optional space-based partitioning**: You can also partition by a second dimension (e.g., by device ID or region) for high-cardinality scenarios
- **Transparent query routing**: Your queries see one table, but TimescaleDB routes them only to relevant chunks

---

## How chunking works

Imagine you have sensors sending temperature readings. With a hypertable using daily chunks:

```
sensor_readings (hypertable)
├── 2025-01-01 chunk (500MB)
├── 2025-01-02 chunk (520MB)
├── 2025-01-03 chunk (510MB)
└── 2025-01-04 chunk (490MB) [currently being written to]
```

When you query `SELECT * FROM sensor_readings WHERE time > NOW() - INTERVAL '1 day'`, TimescaleDB automatically scans only the last chunk(s), skipping the rest entirely.

**Benefits:**

- Queries are **faster** because they scan less data
- **Indexing is more efficient** at the chunk level
- **Compression, tiering, and retention policies** work on whole chunks
- **Concurrent writes** are more efficient (multiple chunks can be written to in parallel)

---

[→NEXT PAGE](/learn/tiger-data-academy/tiger-data-101/hypertables/creating-your-first-hypertable/index.md)

[**Creating Your First Hypertable** — Learn the practical steps to create and configure a hypertable in your database.](/learn/tiger-data-academy/tiger-data-101/hypertables/creating-your-first-hypertable/index.md)