We've created a host of code-focused tutorials that help you get started with TimescaleDB.

Most of these tutorials require a working installation of TimescaleDB.

  • Introduction to TimescaleDB: The tried and true tutorial for learning TimescaleDB.
  • Time-series forecasting: Use R, Apache MADlib and Python to perform data analysis and make forecasts on your data.
  • Analyze cryptocurrency data: Use TimescaleDB to analyze historic cryptocurrency data. Learn how to build your own schema, ingest data, and analyze information in TimescaleDB.
  • Analyze intraday stock data: One of the most common uses for time-series data is to collect intraday securities information. Learn how to collect stock data, store it in TimescaleDB, and perform the most common queries.
  • Build custom TimescaleDB dashboards: Learn how to obtain metrics data from TimescaleDB and visualize it using a basic React app.
  • Analyze NFL play-by-play data: Investigate more than 20 million rows of data from the 2018 NFL season that tracks the movement of all players on the field. For each play, gain insights into player performance and potential strategies to find better fantasy football draft picks.
  • Sample datasets: And if you want to explore on your own with some sample data, we have some ready-made datasets for you to explore.
  • Simulate IoT sensor data: Simulate a basic IoT sensor dataset on PostgreSQL or TimescaleDB.
  • psql installation: psql is a terminal-based front-end for PostgreSQL. Learn how to install psql on Mac, Ubuntu, Debian, Windows, and pick up some valuable psql tips and tricks along the way.

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