CeresDB is a timeseries database that aims to handle both timeseries and analytic workloads efficiently.

Motivation

In the traditional timeseries database, the Tag columns (InfluxDB calls them Tag and Prometheus calls them Label) are normally indexed by generating an inverted index. However, it is found that the cardinality of Tag varies in different scenarios. And in some scenarios the cardinality of Tag is very high, and it takes a very high cost to store and retrieve the inverted index. On the other hand, it is observed that scanning+pruning often used by the analytical databases can do a good job to handle such these scenarios.

The basic design idea of CeresDB is to adopt a hybrid storage format and the corresponding query method for a better performance in processing both timeseries and analytic workloads.

How does CeresDB work?

• See Quick Start to learn about how to get started
• For data model of CeresDB, see Data Model
• For the supported SQL data types, operators, and commands, please navigate to SQL reference