Gemit

aCurve Historian

Long-term storage for operational time-series data

aCurve Historian is built for long-term storage of operational time-series data. It is part of aCurve and keeps historical data available where extended history is needed.

Operational data often needs to remain useful long after it was first collected. aCurve Historian is designed to retain time-series history over long periods so teams can return to earlier conditions, compare periods and keep a reliable basis for analysis and reporting.

Why long-term data matters

History is only useful if it is still there

  • 01

    Retain operational history

    Keep a record of how processes and assets have behaved over time.

  • 02

    Investigate past events

    Go back to the data around a past event or deviation.

  • 03

    Compare conditions over time

    Compare current operation with earlier periods over time.

  • 04

    Optimised for historical analytics

    Chunk-based storage and pre-calculated aggregates are designed for efficient retrieval when trends, dashboards and analytics query long historical ranges.

  • 05

    Keep historical data available

    Retain useful historical detail for analysis over time.

How the Historian works

Built around a few technical principles

The Historian groups time-series data into compressed chunks rather than treating every measurement as an isolated row. New data is buffered and validated before being promoted into long-term storage, while pre-calculated aggregates make common historical views available without processing the full raw dataset on every request.
Simplified data flow
  1. Incoming data
  2. Staging
  3. Long-term store
  4. aCurve & API
01

Chunk-based storage

Time-series data is grouped and stored in compressed chunks.

02

Column-wise compression

Stored data is compressed column by column to reduce the space long-term history requires.

03

Staging before long-term storage

New data is buffered and validated before being promoted into compressed chunks.

04

Pre-calculated aggregates

Pre-calculated aggregate tags make common trends and historical summaries available without processing raw data on every request.

Keep data available over time

Preserve operational history in one long-term store

Think of the Historian as a long-term vault for operational history. Data can be retained over long periods and remain available for analysis and comparison.
History from multiple connected systems can be retained in the same long-term store. That gives teams one place to return to when they need to compare current operation with earlier periods or investigate past events.
  • Operational history retained over long periods
  • Older data available for analysis and comparison
  • History from multiple systems can be retained in one long-term store

Fits into the existing environment

Built on familiar technology

Integrated with aCurve
Historian data is available in aCurve alongside other connected sources.
Microsoft SQL Server
The Historian runs on Microsoft SQL Server.
Standard backup workflows
Data can be backed up using standard SQL Server backup workflows.
Access via the aCurve API
Data can be made available to other systems through the aCurve API.