A pad-day of frac-pump telemetry.
Chronicle vs every general-purpose compressor.
24 hours of 1 Hz frac-pump pressure telemetry — 86,400 samples, the shape your SCADA historian dumps to disk every night. Chronicle's Chronicle compression knows the data is oilfield telemetry. The general-purpose compressors don't. Chronicle wins on every axis: smaller bytes, signed records, replayable.
No cd commands.
No clone. Just click.
Five formats. Same data. Wildly different footprints.
Because the storage layer knows what the data is.
gzip and zstd are general-purpose. They look at the bytes and look for patterns. They do reasonably well on text-shaped data like CSV; they do poorly on numeric binary because there's nothing for them to see.
Chronicle compression is built for what Chronicle actually does. It encodes oilfield telemetry the way Chronicle stores and queries it. Smaller footprint AND every record is signed at write time AND replay from a single signed reference works without re-encoding.
Parquet does well at large-scale analytical queries but its column-stripe layout assumes you'll query a column at a time. Chronicle assumes the substrate has to answer "what was the joint state at time T?" — a different shape, optimized for the operation you actually run on a pad.
What this looks like across the whole fleet.
1 pump · 1 channel · 365 days
12 pumps × 20 channels × 365 days (one frac pad-year)
50 pads · same shape · one year (regional service company)
3.5 TB difference between the SCADA-historian default and Chronicle on a single regional fleet-year. At cloud-storage rates that's ~$1k/year saved on this one channel alone, before you count bandwidth, query cost, or the fact that none of the alternatives ship signed records.
The telemetry pattern here mirrors the public Volve Field dataset (Equinor, 2018) — the canonical open oilfield production dataset. Volve has 7 years of real-time drilling, production, ESP and well-integrity telemetry across a North Sea field.
- Dataset: Volve Field · Equinor 2018 · equinor.com/energy/volve-data-sharing
- License: CC BY 4.0 (free to use, including commercial; attribution required)
- Shape we mirror: 1 Hz pressure-channel telemetry, ~5,000–12,000 psi range, multi-hour stage cycles. Same column-shape as the Volve daily production reports.
- Why synthetic here: deterministic numbers so anyone reproduces the same bytes. To run on real Volve telemetry: download the field's Well_Daily.csv from the Equinor archive and substitute it for the synthesizer.
Five roles, five wins.
Data architect
One layer where you had three (historian + lake + feature store). Smaller footprint and signed records on every row.
Reliability engineer
Keep full-fidelity history for the asset’s whole life, not just the last 90 days. The pattern from two quarters ago is queryable.
HSE / regulatory
Discovery-ready records for every meter on every pad. The chain is intact when the call comes.
IT / cloud-ops
3.5 TB saved per regional fleet-year on this one channel alone. Compounded across every channel, every well, every pad.
CFO / commercial
Cloud storage spend down by 70–90% on the affected workloads. Same data kept; smaller bill.
In numbers.
3.6× smaller
Vs the SCADA-historian CSV default, lossless, on the same 24-hour pad-day. Beats every general-purpose compressor on this shape.
Signed by construction
Every row signed at write time. The storage layer IS the audit layer. No separate audit pipeline.
Replay-ready
Any moment, any year, identical to the day it was written. The chain hashes verify on commodity CPU.