"High-Performance Data Stores for Markets: Applied Techniques with kdb+ and ClickHouse"
Modern electronic markets generate torrents of time-sensitive data, and the firms that can store, query, and interpret that data fastest gain a decisive edge. This book is written for quantitative developers, data engineers, and trading technologists who need to build and operate serious market data platforms—not experiments. It speaks equally to kdb+ veterans looking to adopt ClickHouse and to engineers from the broader data ecosystem who must meet sub-millisecond SLAs for market analytics.
Through a carefully layered progression, the book connects low-level systems foundations—Linux I/O, CPU caches, NUMA, and networking—to columnar database design, ingestion pipelines, and temporal analytics. You will learn how to model market microstructure data, implement reliable tick and order-book feeds, and exploit the strengths of both kdb+ and ClickHouse: from q idioms, as-of joins, and kdb+tick, to MergeTree engines, materialized views, and distributed SQL. Along the way, you will develop a rigorous performance-engineering toolkit, covering benchmarking, profiling, observability, and capacity planning, and you will apply this knowledge to concrete use cases such as limit-order-book analytics, TCA, backtesting, and real-time risk.
The material assumes solid experience with Linux, at least one programming language, and basic SQL, but no prior exposure to kdb+ or ClickHouse. Emphasizing practical patterns over vendor marketing, it offers implementation-ready architectures, operational playbook
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Da: preigu, Osnabrück, Germania
Taschenbuch. Condizione: Neu. High-Performance Data Stores for Markets | Applied Techniques with kdb+ and ClickHouse | Thomas V. Trex | Taschenbuch | Trading System Architecture & DevOps | Englisch | 2025 | NobleTrex Press | EAN 9798896652267 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Codice articolo 135842033
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