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Data Points Storage

Overview​

Data Points Storage is a database designed to store time-series data. It is optimized for handling large-scale datasets and is ideal for querying historical data, such as fetching the last 10k data records, filtering by a defined time range (e.g., start 20/05/2024 stop 20/06/2024), or performing calculations like max, min, sum or average.

See the Data Point structure below:

  • Variable: A human-readable name or label for the object.
  • Value: A custom value field
  • Time: A timestamp indicating the time
{
  "variable": "temperature",
  "value": 23.5,
  "time": "2023-10-15T14:30:00Z"
}
tip

Valeiot Data Points follow a specific structure (presented above) that must be followed to ensure they can be stored in the Data Points Storage. To learn more about the Data Point structure, read the section Valeiot Data Point.

To access the Data Points Storage, select the Data Source you wish to view and locate the table under the Data Points tab.

console-datapoints

Key Characteristics​

  • Immutable: Once created, Data Points cannot be edited, only deleted.
  • Data Retention System: Data Points have a configurable time-to-live (TTL) based on the Data Retention policy. Data older than the specified retention period is automatically removed (e.g. if the Data Retention is set to 30 days, all data older than 30 days - based on the Data Point's time property - will be automatically removed).
  • Efficient & Robust: Designed to efficiently store and retrieve large volumes of time-series data.

Use Cases​

  • Storing millions of Data Points from IoT sensors (e.g., temperature, humidity, pressure, location).
  • Logging activities, application and system metrics over time (e.g., user activity, device logs).
  • Getting the mean, average, maximum or minimum of a specific variable (e.g. speed).

Bucket​

Data Points are associated with a bucket. When creating a new Data Source, you must select a bucket identified by bucket_id. Each bucket has unique properties, such as retention time and chunk intervals. For detailed setup instructions, see the Bucket section.

Data Retention​

Data Points have a time-to-live (TTL) in the system, determined by the Data Retention configuration. For example, if the Data Retention is set to 30 days, all data older than 30 days (based on the Data Point's time property) will be automatically removed. To learn more, read the section on Data Retention.