Building a Scalable Tick Data Architecture

Storing and querying petabytes of raw tick data requires specialized time-series databases. We compare kdb+, InfluxDB, and ClickHouse.

Relational databases like PostgreSQL are excellent for transactional integrity, but they crumble under the weight of high-frequency tick data. When an exchange generates billions of messages per day, researchers require specialized column-oriented time-series databases to query historical price action efficiently.

HarvestGroup360’s internal historical repositories are built on an optimized ClickHouse architecture, allowing our partners to query years of unaggregated tick data in milliseconds. Whether you are using kdb+/q for localized memory-mapped analytics or querying our cloud endpoints, understanding data structuring and partitioning is essential for rapid backtesting iteration.