---
title: Features and Comparison | Tiger Data Docs
description: Compare TimescaleDB features with the competition
---

**Tiger Data 101** → TimescaleDB | **Section:** What is TimescaleDB? | **⏱ Time:** \~3 min

## Key features at a glance

| Feature                     | What it does                                                     |
| --------------------------- | ---------------------------------------------------------------- |
| **Hypertables**             | Automatic time-based partitioning under a single table interface |
| **Hypercore**               | Columnar storage + compression for cold data (10–40x savings)    |
| **Continuous Aggregates**   | Auto-refreshing materialized rollups for fast analytics          |
| **Data Tiering**            | Move old data to cheaper object storage (e.g., S3) automatically |
| **Retention Policies**      | Auto-drop data older than a defined period                       |
| **Full SQL**                | JOINs, CTEs, window functions, indexes, all of standard Postgres |
| **Native time functions**   | `time_bucket()`, `first()`, `last()`, `histogram()` and more     |
| **High ingest performance** | Optimized for append-heavy write patterns                        |

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## TimescaleDB vs. the alternatives

|                                | TimescaleDB               | InfluxDB                 | ClickHouse         | Plain Postgres            |
| ------------------------------ | ------------------------- | ------------------------ | ------------------ | ------------------------- |
| **SQL support**                | Full                      | Limited (Flux/InfluxQL)  | SQL-like           | Full                      |
| **PostgreSQL compatible**      | Yes (it *is* Postgres)    | No                       | No                 | Yes                       |
| **Time-series optimized**      | Yes                       | Yes                      | Partial            | No                        |
| **Columnar storage**           | Yes (hypercore)           | Yes                      | Yes                | No                        |
| **Continuous Aggregates**      | Yes                       | Yes                      | Materialized Views | Manual                    |
| **JOINs with relational data** | Yes                       | Limited                  | Yes                | Yes                       |
| **Ecosystem (ORMs, tools)**    | Entire Postgres ecosystem | Telegraf/Grafana focused | Growing            | Entire Postgres ecosystem |

**The key differentiator:** TimescaleDB gives you purpose-built time-series performance without abandoning the PostgreSQL ecosystem you (and your team) already know.

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[Real-World Applications](/learn/tiger-data-academy/tiger-data-101/what-is-timescaledb/real-world-applications/index.md)

[See how TimescaleDB powers data-intensive applications across industries and real-world use cases.](/learn/tiger-data-academy/tiger-data-101/what-is-timescaledb/real-world-applications/index.md)