One Pager Cheat Sheet

• Time-series databases have rapidly become more popular than other database models in the last two years, making them a subject of worth studying due to their differentiating features and benefits.
• Time-series data refers to data collected over a set period, and its processing involves five different steps - Data Model, Stream Computing, Data Storage, Metadata retrieval and Data Analysis.
• The time-series frequency refers to the rate at which data is collected over a given period.
• A Time-series Database (TSDB) is a specialized database optimized for handling large volumes of time-stamped data that allows for retrieval and analysis of data through concurrently stored variables.
• A Time-Series Database (TSDB) is designed to store and query time-stamped (time, value) pairs and measure sequential and concurrent events.
• Choosing the right database for your data needs is key, and understanding the differences between Time-Series Database and Relational Database makes this decision easier.
• Time-Series Databases (TSDBs) have the ability to insert a high volume of data and do not have SQL support, which makes them well-suited for monitoring systems over time with cost savings and efficient data processing of analytical and reporting data sets.
• The database industry is mainly composed of time-series databases, such as InfluxDB, Prometheus, TimescaleDB and Graphite, which provide different solutions for collecting, storing and querying real-time streams of time series data.
• InfluxDB is a time-series database built with Go that enables scalability and simple integration for collecting, storing, querying, visualizing, and acting on data.
• Time-series databases offer a range of uses such as accessing IoT data, forecasting financial trends, monitoring web services, sales forecasting, and detecting anomalies using virtualization and automated techniques.
• Time-series databases provide the tools to visualize and detect outliers for anomaly detection, allowing organizations to track and uncover past changes, monitor real-time changes, and forecast future occurrences by understanding changes in data over time.
• In the coming future, TSDBs will be an essential component in almost every industry, due to the expanding demand of real-time events caused by the incorporation of IoT/smart devices into everyday life.
• You learned about time-series databases (TSDBs), their different use-cases and various popular TSDBs in the market.