Home Up PDF Prof. Dr. Ingo Claßen
Slide 1: TimescaleDB: Scalable SQL for Time-Series Data

Slide 1: TimescaleDB: Scalable SQL for Time-Series Data

  • Open-source time-series database
  • Built as a PostgreSQL extension
  • Combines relational reliability with time-series performance

Slide 2: Origins \& Motivation

  • Launched in 2018
  • Responds to the need for efficient time-series data handling
  • Maintains SQL compatibility for ease of adoption

Slide 3: Core Architecture

  • Hypertables: Virtual tables partitioned for scalability
  • Chunks: Underlying physical partitions by time (and optionally space)
  • Transparent to users-standard SQL interface

Slide 4: Partitioning Strategy

  • Partitions by time interval and optional space key (e.g., device ID)
  • Optimizes both write and read operations
  • Enables efficient data retention and query performance

Slide 5: Key Features

  • Full SQL support (PostgreSQL ecosystem)
  • Advanced compression for storage efficiency
  • Continuous aggregates for real-time analytics
  • Distributed hypertables for horizontal scaling

Slide 6: Performance Optimizations

  • SIMD vectorization for fast analytics
  • Dense indexes for columnstore (hypercore)
  • Efficient refresh of continuous aggregates
  • Recent releases focus on analytical query speed

Slide 7: Distributed Architecture

  • Access nodes \& data nodes for scaling out
  • Elastic scaling-no redistribution of existing data
  • Partitioning adapts as new nodes are added

Slide 8: Recent Developments

  • Low-downtime live migrations (production-ready)
  • Timescale Cloud: AWS Transit Gateway, CSV import, replica metrics
  • Enhanced MySQL import and UI chunk management

Slide 9: Key Use Cases

  • IoT: Handles high-volume, multi-device data
  • Monitoring: DevOps metrics, logs, and traces
  • Finance: Trading, risk management, analytics
  • Machine Learning: Stores and aggregates training data

Slide 10: Implementation Considerations

  • Flexible data modeling: wide-table or narrow-table
  • Partitioning strategy critical for scaling
  • Integrates seamlessly with BI and analytics tools

Slide 11: Conclusion

  • Combines SQL familiarity with time-series power
  • Robust, scalable, and actively developed
  • Ideal for organizations needing high-performance time-series analytics

Slide 12: Learn More

  • timescale.com
  • Documentation, tutorials, and open-source community

Tip: Add visuals such as architecture diagrams, performance graphs, or real-world use case screenshots to enhance engagement. Let me know if you’d like slide notes or specific visuals for any slide!