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Claude Monet, Stacks of Wheat (End of Summer), 1890 to 1891: two wheat stacks in a field at the end of summer

Every hour of the field, kept.

Sheaf is time-series storage that keeps every reading at full resolution, for as long as you need it.

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Time-series storage

Monet painted the wheat stacks outside his house at Giverny around twenty-five times in 1890 and 1891, at every hour and in every season. Sheaf keeps your metrics the way he kept that field: every moment, nothing averaged away.

Claude Monet, Stacks of Wheat (End of Day, Autumn), 1890 to 1891: two stacks glowing pink in low autumn light

Send it as it happens.

Ingest

Point agents, sensors and services at one endpoint. Sheaf takes Prometheus remote write, OpenTelemetry and line protocol, and files late data under its own timestamp.

Claude Monet, Stack of Wheat, 1890 to 1891: a single stack in a snowy field under a pale winter sky

Nothing is thrown away.

Storage

Readings are kept at the resolution they arrived. Columnar compression keeps per-second data small enough to hold for years, so you never roll it up and lose the detail.

Claude Monet, Stacks of Wheat (Sunset, Snow Effect), 1890 to 1891: two stacks in snow under an orange sunset

Ask about any hour.

Query

Query in SQL or PromQL. Compare this morning with the same morning three winters ago, without building a rollup table first.

Claude Monet, Stack of Wheat (Thaw, Sunset), 1890 to 1891: a dark stack against thawing ground at sunset

Pay for what you keep.

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Pricing

Storage is billed per gigabyte after compression. Ingest and queries are free, and a free cluster keeps thirty days of data with no end date.