InfluxData[1], a time-series database platform provider that already has distinct cloud and open source/on-premises versions, is adding to the stew. It is announcing upgrades to the 2.0 generation of the open source platform that includes some features borrowing from its cloud offering, a smattering of incremental updates, and the announcement of a new open source project that will extend InfluxData's reach to cloud object storage.
The open source platform has now added support for Flux[2], the GUI-based, scripting-oriented query language initially introduced with the InfluxDB Cloud[3] 2.0 platform last spring. It's very much a departure from the original InfluxQL[4] that was a more declarative SQL-like language. It's also a departure from rivals like Timescale[5] and Amazon Timestream[6] that have heavily embraced SQL
InfluxData's rationale is that a scripting-oriented language, even if it is simplified with a drag and drop front end, is a lot more powerful when building analytic queries on time series data. Nonetheless, InfluxData is not pulling the plug on InfluxQL. Hold that thought.
Also part of this release, InfluxData is releasing jumpstart templates, which consist of single file-monitoring configurations for common use cases such as network and IoT sensor monitoring. This comes from a strategy of meeting users where they live – may as well make core use cases easier.
And then there is announcement of yet another new front in the war. InfluxData is unveiling IOx. It would extend the platform's reach to data stored in Parquet format in cloud object storage. As envisioned, IOx would embrace a modern cloud-native architecture by separating storage from compute. Storage would act as the durability layer, while query, ingest, and indexing servers run in stateless Kubernetes clusters, with a management layer up