What is a Time Series Database?
Time-series databases are designed for storing, accessing, and examining data points categorized by time. They excel in managing time-stamped or time-series data derived from sensors, IoT devices, server metrics, financial market data, and any other time-sensitive information.
Time-series databases offer specialized features and structures designed for time-series data. These functionalities facilitate swift data inserts, effective time-based inquiries, and the downsampling/aggregation of data across time intervals.
Time Series Database vs Relational Database: Top Differences
Choosing between a time-series database and a relational database isn’t merely a matter of data storage location. It’s pivotal for shaping your organization’s data handling practices — it’s about enhancing how you extract insights from your data. This decision significantly impacts speed, efficiency, and the precision of your operations.
Consider the potential: smoother operations, swifter decision-making, and a competitive edge in your sector. This is the influence of selecting the correct database. However, to maximize its services, it’s important to understand the differences between these databases and leverage their different strengths to your benefit.
This article gives you a brief discussion between time series databases and relational databases. We will try to keep it simple, breaking down the terms and helping you choose the right option for your requirements.