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timescaledb-tiger-architect

Design TimescaleDB hypertables, chunk sizing, compression, retention, and Iceberg/S3 sync policies.

Updated Nov 25, 2025
Search Tags:#compression#time-series#iceberg#timescaledb#continuous-aggregates#hypertable#chunk-sizing
One-click install
npx skills add https://github.com/filimorniga-ux/farmacias-vallenar-suit --skill timescaledb-tiger-architect
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: timescaledb-tiger-architect
Source: https://github.com/filimorniga-ux/farmacias-vallenar-suit/tree/main/.agent/skills/timescaledb-expert
Command: npx skills add https://github.com/filimorniga-ux/farmacias-vallenar-suit --skill timescaledb-tiger-architect

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates guesswork and costly mistakes when designing and operating high-ingest time-series databases by prescribing hypertable design, chunk sizing, query optimization, compression, retention, and cloud-tiering strategies tailored for TimescaleDB and Tiger Cloud.

Core Features & Use Cases

  • Hypertable Best Practices: Ensures append-only temporal data is modeled as hypertables and avoids manual Postgres partitioning pitfalls.
  • Chunk Sizing & Memory Fit: Calculates chunk_time_interval using the 25% RAM rule to prevent index thrashing and optimize active-chunk performance.
  • Query & Read Optimization: Advises enabling chunk skipping for correlated columns and prescribes continuous aggregates with incremental refresh policies for real-time analytics.
  • Lifecycle Management: Recommends compression segmentby/orderby settings, automated compression policies, and chunk-based retention (DROP CHUNK) instead of row-level deletes.
  • Cloud Tiering (Tiger Lake / Iceberg): Guides configuring Iceberg/S3 synchronization for long-term, queryable cold storage.

Quick Start

Use the timescaledb-tiger-architect skill to analyze ingest rates and recommend hypertable chunk_interval, continuous aggregate policies, compression and retention settings, and S3/Iceberg sync for cold data.

Frequently Asked Questions about timescaledb-tiger-architect

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I calculate chunk_time_interval for TimescaleDB hypertables to fit available RAM?▼

Calculate TimescaleDB chunk_time_interval using the 25% RAM rule to prevent index thrashing and optimize active-chunk performance for high-ingest telemetry.

What is the best way to configure continuous aggregates and refresh policies for real-time analytics in TimescaleDB?▼

Configure continuous aggregates with incremental refresh policies to precompute time-series data, enabling fast real-time analytics queries without reprocessing the entire hypertable history.

How does compression segmentby and orderby work for TimescaleDB lifecycle management?▼

TimescaleDB compression uses segmentby to group correlated data and orderby to sort within groups, enabling chunk-based retention via DROP CHUNK and automated compression policies instead of row-level deletes.

Can I use Iceberg and S3 synchronization for cold storage tiering with TimescaleDB?▼

Yes, you can configure Iceberg and S3 synchronization to establish queryable cold storage, moving older time-series chunks out of the active database while keeping them accessible for long-term analysis.

When should I enable chunk skipping for correlated columns in time-series hypertables?▼

Enable chunk skipping for correlated columns when query patterns frequently filter by specific metadata, allowing the database to skip scanning irrelevant chunks and significantly accelerating telemetry retrieval.

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