KairosDB vs Prometheus: What are the differences?

Introduction:

KairosDB and Prometheus are both popular time series databases used for monitoring and analytics. Despite serving similar purposes, they have key differences that set them apart.

1. Data Model: KairosDB stores data as points in a series, while Prometheus uses a multidimensional data model based on key-value pairs called time series. This difference in data modeling can impact the querying and manipulation of data in both databases.

2. Query Language: KairosDB uses a RESTful API for querying data, while Prometheus uses PromQL, a powerful query language specifically designed for time series data. The syntax and capabilities of these query languages vary, affecting how users interact with and retrieve data from the databases.

3. Scalability: Prometheus is designed for monitoring scenarios with a focus on performance and scalability, while KairosDB can handle larger datasets and more complex analytics requirements due to its architecture optimized for those capabilities. This distinction is crucial for users with varying data storage and processing needs.

4. Alerting: Prometheus has built-in alerting capabilities, allowing users to define and trigger alerts based on query results. KairosDB does not have native alerting features, requiring users to integrate with external tools for alerting functionality. This difference influences the monitoring and notification processes in each database.

5. Data Retention: KairosDB supports configurable data retention policies, allowing users to define rules for data retention based on time or size. In contrast, Prometheus follows a more limited retention model, focusing on high-cardinality data and leveraging efficient storage techniques. This difference affects how historical data is managed and stored in the databases.

6. Ecosystem Integration: Prometheus has a strong ecosystem of exporters and integrations with popular tools, making it a leading choice for cloud-native environments and DevOps practices. KairosDB, while versatile, may require more customization and integration efforts to fit into modern monitoring and analytics pipelines.

In Summary, KairosDB and Prometheus differ in their data models, query languages, scalability, alerting capabilities, data retention policies, and ecosystem integration, offering users distinct choices for time series database solutions.