We've created a host of code-focused tutorials that will help you get
started with TimescaleDB.
Most of these tutorials require a working installation of TimescaleDB.
Common scenarios for using 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.
Integrating with Grafana
- Sample data sets: And if you want to explore on your own
with some sample data, we have some ready-made data sets 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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