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Overview

RocksDB provides comprehensive statistics for monitoring database performance, diagnosing issues, and tuning configuration. The Statistics object collects counters and histograms across all database operations.
Enabling statistics is essential for production deployments to understand performance characteristics and troubleshoot issues.

Creating Statistics

From statistics.h:859-860:
Basic setup:

Statistics Levels

From statistics.h:752-775, control overhead vs. detail:
Setting the level:
kAll includes mutex wait time measurement which can reduce scalability under high concurrency.

Tickers (Counters)

From statistics.h:31-587, RocksDB tracks over 100 counters:

Block Cache Statistics

Calculate hit rate:

Bloom Filter Statistics

Measure filter effectiveness:

Read/Write Statistics

Compaction Statistics

Compression Statistics

From statistics.h:251-283:

Stall Statistics

Histograms

From statistics.h:604-733, track latency distributions:

Reading Histogram Data

From statistics.h:738-750:
Example usage:

Accessing Statistics

Get Individual Ticker

From statistics.h:801-806:

Reset Statistics

From statistics.h:829-830:

Get All Tickers as Map

From statistics.h:839-842:

String Representation

From statistics.h:833-837:

Database Properties

Beyond Statistics, query runtime properties:

Common Properties

Monitoring Patterns

Periodic Statistics Dump

Custom Monitoring Loop

Latency Monitoring

Write Amplification Tracking

Performance Overhead

Minimal Overhead Configuration

Maximum Detail (Debug)

Most tickers have negligible overhead. Histograms and detailed timers add measurable but usually acceptable overhead.

Integration with Monitoring Systems

Prometheus Exporter

Troubleshooting with Statistics

High Write Amplification

Check:

Cache Inefficiency

Check:

Write Stalls

Check:

Best Practices

Always enable statistics in production with at least kExceptDetailedTimers level.
  1. Use appropriate stats level: Balance overhead and detail
  2. Monitor key metrics: Hit rate, write amp, latency, stalls
  3. Set up alerting: Alert on anomalies (high P99, low hit rate)
  4. Periodic dumps: Use stats_dump_period_sec for logging
  5. Reset when needed: Call Reset() after major events
  6. Correlate with workload: Understand metrics in context of operations

See Also