Data model

As a relational database supporting full SQL, TimescaleDB supports flexible data models that can be optimized for different use cases. This makes TimescaleDB somewhat different from most other time-series databases, which typically use “narrow-table” models.

Specifically, TimescaleDB can support both wide-table and narrow-table models. Here, we discuss the different performance trade-offs and implications of these two models using an Internet of Things (IoT) example.

Imagine a distributed group of 1,000 IoT devices designed to collect environmental data at various intervals. This data could include:

• Identifiers: device_id, timestamp
• Metadata: location_id, dev_type, firmware_version, customer_id
• Device metrics: cpu_1m_avg, free_mem, used_mem, net_rssi, net_loss, battery
• Sensor metrics: temperature, humidity, pressure, CO, NO2, PM10

For example, your incoming data may look like this:

Now, let’s look at various ways to model this data.