TimescaleDB vs. InfluxDB: Purpose built differently for time-series data

In this comparison, TimescaleDB and InfluxDB are evaluated across various dimensions such as data model, query language, reliability, performance, ecosystem, operational management, and company/community support. The study reveals that TimescaleDB has a relational data model, SQL query language, and relies on PostgreSQL's robustness for reliability, which results in better performance, especially with high cardinality datasets. In contrast, InfluxDB has a custom tagset data model, Flux query language, and is more limited in its scalability and indexing capabilities, leading to slower performance, particularly with large datasets. The comparison also highlights the importance of ecosystem support, operational management, and company/community support in choosing a time-series database, with TimescaleDB offering a broader range of tools and resources, while InfluxDB's ecosystem is more limited and gated behind an enterprise license.