Time series

The task is the Time Series Benchmark Suite on its CPU data set. The queries are the ones a monitoring stack asks: the newest reading per sensor, a twelve-hour aggregate, a double group-by over host and hour, a high-usage filter, and a grouped, ordered, limited query of the shape a dashboard issues.

The ingest rate is its own column, separate from every query, because the two say nothing about each other. An engine with more than one way to store time series is measured through each way, not only the faster one.

Still being measured at this version. This table appears here when its run finishes.

The rules every result follows are in the methodology. The settings for each engine are on the engines page. If one is wrong, tell us.

• Tables: Documents and structured query language (SQL) analytics.
• Graphs: Interactive and analytical queries on a social network graph.
• Vectors: Dense and sparse vector search, with recall beside every latency.
• Cross-model: One operation across a vector, a graph edge, and a document.
• Lifecycle: Opening, closing, deployment boundaries, and what waiting for the disk costs.