Time series data¶

Use CrateDB to store and query massive amounts of time series data.

Time series data represents one of the fastest-growing data types across industries, from IoT sensors and industrial equipment to application metrics and financial transactions. The challenge lies not just in handling the sheer volume of incoming data points, but in maintaining query performance across both real-time streams and historical datasets while managing storage costs effectively.

Traditional databases struggle with the unique characteristics of time series workloads: high write throughput, time-based queries spanning variable ranges, the need for downsampling and aggregation, and retention policies that balance storage with analytical requirements. Many organizations find themselves cobbling together multiple systems—one for ingestion, another for querying, and yet another for long-term storage—creating operational complexity and data silos.

CrateDB handles time series data natively through its distributed architecture, combining high-speed ingestion with powerful SQL analytics across any time range. Its partitioning capabilities enable efficient data lifecycle management, while built-in functions for downsampling, interpolation, and time-window operations simplify complex analytical tasks. You can query billions of data points in seconds, whether analyzing recent trends or exploring patterns across years of historical data.

With CrateDB, compatible to PostgreSQL, you can do all of that using plain SQL. Other than integrating well with commodity systems using standard database access interfaces like ODBC or JDBC, it provides a proprietary HTTP interface on top.

Fundamentals

Basic introductory tutorials about using CrateDB with time series data.

What’s inside: Getting Started, Downsampling and Interpolation, Operations: Sharding and Partitioning.

Time series fundamentals with CrateDB

Advanced analysis

Advanced time series data analysis with CrateDB.

What’s inside: Exploratory data analysis (EDA), time series decomposition, anomaly detection, forecasting.

About time series analysis

Video tutorials

Educational videos about time series data and CrateDB.

What’s inside: Time series introduction. Importing, exporting, and analyzing. Industrial applications.

Video tutorials about time series with CrateDB

Academy » Advanced time series

CrateDB Academy is a learning hub dedicated to empowering data enthusiasts with the tools and knowledge to harness the power of CrateDB.

What’s inside: Data manipulation and visualization. Data Storage. Importing. Machine Learning on Time Series Data: EDA, Decomposition, AutoML.

Academy Resources: Advanced Time Series