Historical Data Logging Storage Estimator
Calculate required hard drive or SQL database storage space over time.
Historian Parameters
Estimated Storage
* Note: This is raw data size. Actual database size will vary depending on the SQL/NoSQL engine overhead, indexing, and compression algorithms used.
Understanding SCADA Historian Data Storage
Estimating storage requirements for an industrial SCADA historian is critical for long-term data retention and system performance. Due to the high frequency of data logging from PLCs and sensors, calculating the required disk space prevents unexpected system outages.
The Core Storage Formula
A standard starting point for determining raw storage capacity is:
Storage = (Tags × Samples per Second × Bytes per Sample × Time Interval) ÷ Compression Factor
Historians rely heavily on lossless compression algorithms, which can reduce storage footprints by ratios ranging from 3:1 to 40:1, depending on data volatility.
Key Factors Influencing Storage
- Deadbanding: Exception-based logging records values only when they change beyond a defined threshold, drastically cutting down storage needs compared to cyclic logging.
- Data Volatility: Highly fluctuating process variables compress poorly, while stable states compress efficiently.
- The “Double It” Rule: Industry best practice dictates calculating the raw estimate and then provisioning an additional 25% to 50% buffer to handle unexpected noise, metadata overhead, and future expansion.
Always maintain at least 20% free disk space to ensure optimal database indexing and retrieval speeds.