Introduction to Time Series Databases

Overview

• Definition and purpose of time series databases.
  • Designed specifically for time series data storage.
  • Built from the ground up to accommodate unique properties of time series data.

Understanding Time Series Data

Definition

• Sequence of data points over a time interval.
• Data is typically collected in increasing time order.

Example Data Structure

• Table with fields: ID, Timestamp, Air Quality, Temperature.
• Every row has a timestamp, making it time series data.

Examples

• Sensor Data: Emits data every second/millisecond.
• Weather Data: Measurements over time like temperature.
• System Monitoring Data: Metrics over time, e.g., CPU usage.
• Website Activity Data: Tracks user activity and flow.
• Stock Prices: Price changes over time.

Unique Characteristics of Time Series Data

High Write Throughput

• Designed for frequent data entries (e.g., sensor or stock data).
• Writes can be regular or irregular.

Data Compression

• High similarity in data rows requires efficient compression.

Large Range Scans

• Common to scan large data sets for summaries (e.g., average stock prices over a month).

Write to Latest Time Entry

• Generally deals with current data rather than historical data.

Native Support for Aggregations

• Supports summaries, aggregations, and roll-ups efficiently.

Example Queries for Time Series Databases

• Daily stock prices averages.
• Daily average temperature changes.
• Monthly unique website visits.
• Identify highest revenue months over years.
• Average Uber ride prices by city.

Popular Time Series Databases

• Quest DB, Time Scale DB, Influx DB: Easily deployable, some are open source.
• Amazon Timestream: Managed cloud service by AWS.
• Cassandra: Nosql database, requires custom data modeling for performance.

Conclusion

• Time series databases are essential for efficiently handling time-associated data.
• Future tutorials will dive deeper into specific databases and performance comparisons.

• Next Steps: Await future videos for detailed tutorials on data ingestion and query performance comparisons.
• Questions: Engage via comments for any clarifications or queries.