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From 14TB to 700GB: Optimizing Database Storage for Real-Time Monitoring

A shortened look at 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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