InfluxDB vs KairosDB: What are the differences?

Introduction

InfluxDB and KairosDB are both popular time series databases that are widely used for storing and analyzing time-stamped data. While they both serve the same purpose, there are several key differences between the two.

1. Data Model: InfluxDB adopts a tag-based data model, where data is organized into measurements, tags, and fields. Measurements represent a specific metric or data value, tags provide metadata for filtering and grouping, and fields store the actual data values. On the other hand, KairosDB uses a key-value pair data model, where the data is stored as a set of key-value pairs without the concept of tags or fields.

2. Query Language: InfluxDB provides a powerful query language called InfluxQL, which allows users to perform complex queries and aggregations on the time series data. InfluxQL supports various functions, joins, and group by operations. In contrast, KairosDB primarily relies on a simple JSON-based query language, which doesn't offer the same level of flexibility and functionality as InfluxQL.

3. Scalability: InfluxDB is designed to be highly scalable and can handle large volumes of data and high write and read throughput. InfluxDB achieves scalability through its clustered architecture and the ability to distribute data across multiple nodes. On the other hand, KairosDB doesn't have built-in clustering capabilities and may require external solutions for achieving scalability in highly demanding environments.

4. Ecosystem and Integrations: InfluxDB has a vibrant community and a rich ecosystem of integrations, libraries, and tools. It provides various client libraries and plugins for different programming languages and supports popular data visualization and monitoring tools. KairosDB, while being a capable time series database, has a smaller community and a less extensive ecosystem compared to InfluxDB.

5. Data Retention and Downsampling: InfluxDB offers built-in mechanisms for data retention and downsampling, which allow users to automatically expire or downsample older data to conserve storage space and optimize querying performance. KairosDB doesn't provide native support for data retention and downsampling, and users may need to implement custom solutions to achieve similar functionality.

6. Data Replication and High Availability: InfluxDB offers various replication options, including asynchronous and synchronous replication, to ensure data durability and high availability. It provides the ability to configure data replication across multiple clusters and data centers. KairosDB, on the other hand, doesn't have built-in replication mechanisms and may require additional setup and configuration for achieving data replication and high availability.

In summary, InfluxDB and KairosDB differ in their data models, query languages, scalability capabilities, ecosystems, data retention and downsampling mechanisms, and data replication and high availability features. These differences should be considered when choosing the appropriate time series database for a specific use case.