{ "item_title" : "High-Performance Data Stores for Markets", "item_author" : [" Thomas V. Trex "], "item_description" : "High-Performance Data Stores for Markets: Applied Techniques with kdb+ and ClickHouseModern 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", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/9/79/889/665/9798896652267_b.jpg", "price_data" : { "retail_price" : "49.99", "online_price" : "49.99", "our_price" : "49.99", "club_price" : "49.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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