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Treliant: A Cloud-Native Trade Analytics App in 10 Lines of Code with kdb Insights
5 September, 2023
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3 Real Capital Markets Examples that Unlock GenAI Value
10 July, 2023
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Tackling Data Challenges with KX and Capco: A Fresh Perspective
30 June, 2023
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OAuth2 authorization using kdb+
28 June, 2023
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Accelerating Python Workflows using PyKX
28 June, 2023
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Slim Down That Python with PyKX
27 June, 2023
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PyKX: Run Python, q the Speed
14 June, 2023
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10 Takeaways from Gartner Data & Analytics Summit, London, May 22-24
25 May, 2023
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Business Intelligence: Engines & Horses for Courses
22 May, 2023
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KX & Snowflake: Empowering Snowflake with Up to 100x Faster and More Efficient Vector and Time Series Analytics
19 May, 2023
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The Montauk Diaries
17 May, 2023
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Stop Stuffing Your Time Series Data into Your Data Warehouse Like it’s Your Sock Drawer
21 April, 2023
Benchmarking KDB-X and KDB-X Python against Polars, DuckDB, ClickHouse, and Pandas
What the KX NYSE TAQ benchmark numbers actually say about memory need, query expressiveness and speed, and what we learned implementing 84 capital markets queries in six engines