Brevan Howard Uses QuestDB for Live and Historic Market Data

QuestDB said Brevan Howard is using its open-source time-series database to run live and historic market data workloads. The use case supports systematic trading and pre-trade analysis and focuses on low-latency handling of market data for trading workflows.

QuestDB described the deployment as a way to store market and trade data with low-latency ingestion and querying of tick data and trades at scale. It also tied the approach to resilience requirements for mission-critical data and to access for both live trading and historical research.

QuestDB said it provides low-latency storage and an out-of-the-box pre-trade analysis toolkit that uses native SQL primitives for capital markets, including ASOF JOIN. The toolkit includes time-series joins such as Window Joins and Horizon Joins, and QuestDB said it is built to support resilience for market data.

The company said Parquet support supports lakehouse access for the same market data across live and historical workflows. It also referenced an end-to-end lifecycle covering market data and systematic trading, and it said the system uses open formats to avoid proprietary lock-in.

“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.”

Provided by Globe Newswire on behalf of QuestDB. Click to read original content.