InfluxDB vs TDengine
Detailed comparison of InfluxDB and TDengine: InfluxDB: Time-series database written in Go. It supports SQL-like queries, Flux language for advanced data processing, and has a HTTP API. Supports data retention policies, continuous queries, downsampling, and rollups. Supports high availability clustering, with the ability to scale horizontally. Has a wide range of integrations with tools such as Grafana, Telegraf, and Kapacitor. TDengine: Time-series database written in C++. It supports SQL-like queries, and has a HTTP API. Supports data retention policies, down sampling, and rollups. Supports high availability clustering, with the ability to scale horizontally. Has a built-in C interface, as well as connectors for various programming languages such as Python, Java, and Go. Offers built-in functions and modules for real-time data processing and analysis. Comparison: Both InfluxDB and TDengine are time-series databases that support SQL-like queries and have a HTTP API. InfluxDB offers Flux language for advanced data processing, while TDengine offers built-in functions and modules for real-time data processing and analysis. InfluxDB supports continuous queries, downsampling, and rollups, while TDengine supports only down sampling and rollups. Both databases support high availability clustering and horizontal scaling. InfluxDB has more integrations with other tools, such as Grafana, Telegraf, and Kapacitor, while TDengine offers connectors for various programming languages such as Python, Java, and Go. Overall, both InfluxDB and TDengine are powerful time-series databases with similar features and capabilities. The choice between them may depend on specific use cases, programming language preferences, and integration requirements.