NEW YORK, July 17, 2026 (GLOBE NEWSWIRE) — QuestDB, the open-source time-series database for capital markets, today announced that Brevan Howard, a global alternative asset manager, is using QuestDB to power its live and historic market data offering, supporting systematic trading and pre-trade analysis. The deployment of QuestDB enables low-latency ingestion and querying of tick data and trades at scale, allowing teams to react to markets fast while meeting the resiliency requirements of mission-critical data.
“Brevan Howard’s systematic trading workload is exactly the high-throughput, low-latency architecture QuestDB was designed for,” said Nicolas Hourcard, CEO of QuestDB. “By combining real-time ingestion, a pre-trade analysis toolkit built for capital markets, and open formats like Parquet for lakehouse access, QuestDB gives trading teams one system covering the full lifecycle of market data and systematic trading.”
QuestDB provides low-latency storage for market and trade data, together with an out-of-the-box pre-trade analysis toolkit featuring native SQL primitives for capital markets, including ASOF JOIN. The toolkit also includes a full suite of time-series joins, including Window Joins and Horizon Joins, and is designed to support the resilience required for mission-critical market data infrastructure. Built on open standards, QuestDB enables the same data to be used across both live trading workflows and historical research without proprietary lock-in.
This deployment highlights how modern time-series architectures built on open standards can support systematic trading workloads, bridging real-time market data and historical analytics, while maintaining performance, resilience, and architectural flexibility.
About QuestDB
QuestDB is the open-source time-series database for demanding workloads, from trading floors to mission control. It delivers ultra-low latency, high ingestion throughput, and a multi-tier storage engine. QuestDB is designed from the ground up to operate close to the hardware, eliminating ingestion bottlenecks and lowering overall hardware requirements. Native support for SQL and open formats such as Parquet keeps data portable and AI-ready, with no vendor lock-in. Learn more at https://questdb.com/.
