timescaledb-tiger-architect

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.