Smart Factory & IoT

10KHz sensor ingestion. Real-time anomaly detection. Predictive maintenance at microsecond latency.

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Why Manufacturers Choose ZeptoDB

10KHz+ Ingestion

Handle high-frequency vibration, temperature, and pressure sensors without data loss.

Real-Time Analytics

Window functions for rolling averages, anomaly detection, and threshold alerts — all in SQL.

Edge to Cloud

Run on edge nodes (ARM Graviton) or cloud clusters. Parquet HDB for long-term storage on S3.

OPC-UA Ready

Industrial protocol support for PLC and SCADA integration (roadmap).

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Use Cases

Predictive Maintenance

• Ingest vibration, temperature, and current sensors at 10KHz+
• Rolling statistics (EMA, stddev, percentiles) for drift detection
• ASOF JOIN to correlate sensor anomalies with maintenance events

Quality Control

• Real-time SPC (Statistical Process Control) with window functions
• Detect out-of-spec measurements within microseconds
• Historical analysis from Parquet HDB for root cause investigation

Energy Monitoring

• Sub-second power consumption aggregation across facility
• Peak demand detection and load balancing analytics
• xbar time bucketing for shift/hourly/daily reports

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Example: Vibration Anomaly Detection

-- Detect anomalous vibration readings using rolling statistics
SELECT
    sensor_id,
    ts,
    vibration,
    ema(vibration, 100) AS ema_100,
    vibration - ema(vibration, 100) AS deviation
FROM sensor_readings
WHERE
    ts > now() - interval '5 minutes'
    AND abs(vibration - ema(vibration, 100)) > 3 * stddev(vibration)
        OVER (PARTITION BY sensor_id ORDER BY ts ROWS 1000 PRECEDING)
ORDER BY deviation DESC

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Deployment Options

Environment	Configuration
Edge (single node)	ARM Graviton, 16GB RAM, local NVMe
Factory floor cluster	3-node cluster, 10GbE, shared Parquet on NAS
Cloud (historical)	Multi-node on EKS, Parquet HDB on S3
Hybrid	Edge for real-time, cloud sync for analytics

See Production Deployment for details.