A See how TimescaleDB helps WaterBridge handle 10,000 data points per second for their oil & gas operations using TimescaleDB. Read the complete story — How WaterBridge Uses TimescaleDB for Real-Time Data Consistency.
From SQL Server to TimescaleDB
WaterBridge manages water infrastructure for oil and gas operations. When their database couldn't handle 5,000-10,000 data points per second across their sensor network, they needed a solution that wouldn't buckle under pressure. And TimescaleDB checked all the boxes.
"The appeal of Timescale was that we only needed to communicate with PostgreSQL. Real-time ingestion is critical for us: the control room trends metrics in real time. Therefore, as soon as data comes in, it must be displayed on the screen without delay, regardless of query execution time."
| Before TimescaleDB | After TimescaleDB + Hypercore |
|---|---|
| 14TB spread across three databases | 700GB across three databases |
| $12,000/month for basic trending | Significant cost reduction |
| Struggling to ingest 5-10K data points/second | Processing 5-10K data points/second with instant visualization |
| 4TB tier limit, no compression | 73TB of raw data compressed to 4TB |
| Query performance degrading | Zero query lag for 24/7 monitoring |
| Selective data filtering required | Full data capture across ~1M metrics |
| Limited control room trends with lag | Real-time monitoring for leak detection |
| No historical data access | Auto-downsampling for all team needs |
| Scaling would triple costs | Supporting ML and predictive maintenance |
Managing millions of data points from sensors? Learn more about how Timescale handles IoT data at scale.
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