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What are the advantages of Influx-iOX compared to Apache Druid? There seems to be much overlap in feature set and target use cases: seperate storage from compute, using parquet for columnar storage, good at analytical workloads on timeseries.

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It looks like Influx-IOx and Apache Druid have many common base building blocks. The main difference is that Influx-IOx is optimized for time series workloads, while Apache Druid is optimized for analytical workloads. While time series workloads can be treated as analytical workloads in most cases, time series databases usually provide specialized query languages such as Flux, InfluxQL, PromQL [1] or MetricsQL [2] that simplify typical queries over time series data.

P.S. Apache Druid should be compared to ClickHouse [3] or similar analytical databases.

[1] https://valyala.medium.com/promql-tutorial-for-beginners-9ab...

[2] https://victoriametrics.github.io/MetricsQL.html

[3] https://clickhouse.tech/

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