Find Hypertable Candidates
Use this skill to analyze an existing PostgreSQL database and identify which tables...
Install
npx skills add timescale/pg-aiguide --skill find-hypertable-candidates -g -a claude-code -y- Repository
- timescale/pg-aiguide1.9k
- Category
- Data and ML
- Updated
- 8d ago
- License
- Apache-2.0
- Context cost
- Mediumabout 2,358 tokens
- Runs scripts
- No, instructions only
What it does
Use this skill to analyze an existing PostgreSQL database and identify which tables should be converted to Timescale/TimescaleDB hypertables. **Trigger when user asks to:** - Analyze database tables for hypertable conversion potential - Identify time-series or event tables in an existing schema - Evaluate if a table would benefit from Timescale/TimescaleDB - Audit PostgreSQL tables for migration to Timescale/TimescaleDB/TigerData - Score or rank tables for hypertable candidacy **Keywords:** hypertable candidate, table analysis, migration assessment, Timescale, TimescaleDB, time-series detection, insert-heavy tables, event logs, audit tables Provides SQL queries to analyze table statistics, index patterns, and query patterns. Includes scoring criteria (8+ points = good candidate) and pattern recognition for IoT, events, transactions, and sequential data.
PostgreSQL Hypertable Candidate Analysis
Identify tables that would benefit from TimescaleDB hypertable conversion. After identification, use the companion "migrate-postgres-tables-to-hypertables" skill for configuration and migration.
TimescaleDB Benefits
Performance gains: 90%+ compression, fast time-based queries, improved insert performance, efficient aggregations, continuous aggregates for materialization (dashboards, reports, analytics), automatic data management (retention, compression).
Best for insert-heavy patterns:
- Time-series data (sensors, metrics, monitoring)
- Event logs (user events, audit trails, application logs)
- Transaction records (orders, payments, financial)
- Sequential data (auto-incrementing IDs with timestamps)
- Append-only datasets (immutable records, historical)
Requirements: Large volumes (1M+ rows), time-based queries, infrequent updates
