From Development to Production

Module: Tiger Data 101 → An Introduction to TimescaleDB
Section: Putting TimescaleDB Into Action
Estimated time: 10–12 minutes total (this page: ~2 minutes)

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Learning objectives

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

• Evaluate TimescaleDB capabilities against specific use cases
• Design solutions that scale from development to production
• Analyze real-world case studies and apply lessons learned

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Development vs. Production

Development

• Single machine TimescaleDB instance
• Standard PostgreSQL client libraries
• Manual data management (compression, tiering, retention)

Production (Tiger Cloud)

• Fully managed service (automated backups, scaling, monitoring)
• High availability with read replicas
• Built-in connection pooling
• Automated lifecycle policies

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Connection Pooling

Essential for applications with many concurrent connections:

Application (1000 connections)
    ↓
PgBouncer (connection pool, 100 actual connections)
    ↓
TimescaleDB

Benefits: Fewer database resources, faster connection recycling

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Schema Design Best Practices

1. Use appropriate time column types:

   • TIMESTAMPTZ for global applications (timezone-aware)
   • TIMESTAMP for local times

2. Denormalize selectively:

   • Store device metadata alongside readings
   • Reduces JOIN overhead

3. Index strategically:

   • (time, tag) composite index for time-filtered, tagged queries
   • (tag, time) for tag-filtered, time-ordered queries

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→NEXT MODULE

Data Lifecycle Management — Learn retention policies, compression, and tiering strategies.