How Companion.energy Reduced Query Latency 25x & Compressed Terabytes to Gigabytes with Tiger Cloud

This account details Companion.energy's migration from Azure PostgreSQL to Tiger Cloud, resulting in significant improvements in query performance, data compression, and overall system architecture. The company operates across Belgium and beyond, managing data from hundreds of customers' distributed systems. Initially, their platform ran on a single Azure PostgreSQL instance, but as data volumes grew, performance issues arose, leading to slow queries and timeouts.

The company faced two major challenges: performance degradation and unsustainable storage costs. They attempted to address these issues by adding more compute and memory to their Azure PostgreSQL instance, but this did not solve the root cause of the problem. The main issue was the lack of compression policies, continuous aggregates, and skip-scan optimizations, which were available in Tiger Cloud's full feature set.

After evaluating alternatives such as MongoDB, InfluxDB, and ClickHouse, Companion.energy decided to commit their entire platform to Tiger Cloud. This decision allowed them to access crucial features like compression policies, continuous aggregates, and skip-scan optimizations, which were not available in Azure PostgreSQL's TimescaleDB extension.

With Tiger Cloud, the company experienced a 25x improvement in query performance, with meter data lookups going from 4,950 milliseconds to just 202 milliseconds. This achievement was made possible by leveraging Tiger Cloud's skip-scan optimizations, which were previously unavailable in their previous database solution. The migration also resulted in faster ingest speeds, lower storage costs, and a cleaner architecture for future growth.