Resources
Curated reading list and references for Tiger Data 101
A curated reference list for the Tiger Data 101 learning path — organized by topic.
Tiger Data Official Documentation
Section titled “Tiger Data Official Documentation”Core concepts
Section titled “Core concepts”- Tiger Data Whitepaper — deep-dive technical architecture
- Glossary — definitions for all key terms
- Understand Capabilities — how TimescaleDB compares to alternatives
Time-series fundamentals
Section titled “Time-series fundamentals”- Time-Series Basics — what time-series data is and why it matters
Hypertables
Section titled “Hypertables”- Understand hypertables
- Create and Configure a hypertable
- Partition a hypertable
- hypertable Indexes
- Optimize Data in hypertables
Hypercore (columnar storage & compression)
Section titled “Hypercore (columnar storage & compression)”Continuous aggregates
Section titled “Continuous aggregates”- Continuous Aggregates Overview
- Understand Continuous Aggregates
- Time and Continuous Aggregates
- Hierarchical Continuous Aggregates
- Real-Time Aggregates
- Materialized hypertables
Tiger Data Blog
Section titled “Tiger Data Blog”- Start on Postgres, Scale on Postgres — TimescaleDB's philosophy and growth path
- Continuous Aggregate Refresh, Demystified: Invalidation, Lookback, and Late-arriving Data — deep-dive on refresh mechanics
Case studies
Section titled “Case studies”- How ControlCom Turns 300+ Million Monthly Facility Data Points into Instant Answers with Tiger Data — IoT & facility management
- All Case Studies — implementations across industries
External Resources
Section titled “External Resources”PostgreSQL foundations
Section titled “PostgreSQL foundations”- PostgreSQL Documentation — official Postgres reference
- PostgreSQL Tutorial — beginner-friendly SQL and Postgres fundamentals
Learning Path Reference
Section titled “Learning Path Reference”| # | Module | Topic | Time |
|---|---|---|---|
| 1 | What is TimescaleDB? | Introduction, architecture, key features | 12–15 min |
| 2 | Working with Time-Series Data | Data modeling and characteristics | 8–10 min |
| 3 | Hypertables | Partitioning, indexing, optimization | 10–12 min |
| 4 | Hypercore | Columnar storage and compression | 8–10 min |
| 5 | Continuous Aggregates | Materialized rollups and refresh policies | 10–12 min |
| 6 | Putting TimescaleDB Into Action | Production design patterns and case studies | 10–12 min |
| 7 | TimescaleDB Core Use Cases | IoT, financial, analytics, industrial, APM, infrastructure | 8–10 min |
| Total course time: | ~60 minutes |
Getting Started Next
Section titled “Getting Started Next”Ready to dive deeper?
- Build tutorials — hands-on projects and quickstarts
- Tiger Data blog — deep-dives and company updates
- Community support — join the TimescaleDB community