Exploring the future of financial data architecture: AI-native financial data foundation, large-scale financial data processing, and enterprise data quality & governance.
Tag: Data Platform
Before I start talking about how effective this architecture can be at reducing infrastructure costs, I should first make the old point that there is really no free lunch. Compared with commercial cloud data platforms and warehouses such as Databricks, BigQuery, and Snowflake, an open lakehouse setup requires significantly more engineering effort to build, operate, … Continue reading S3 + Parquet + Iceberg + Trino: A Poor Man’s Market Data Platform
What makes me buy into DolphinDB: Friendly DolphinDB – Cross-Exchange Arbitraging Case Speedy DolphinDB – Why is DolphinDB so fast? Robust DolphinDB – Reliable, Scalable, Resilient, Consistent, and Monitorable Cost Effective DolphinDB – Worth the Money DolphinDB – An Integrated Financial Data Platform, Not Just a Time-Series Database As a high-performance database built for business-critical financial applications … Continue reading Robust DolphinDB – How does DolphinDB Achieve Scalability, Reliability, Resilience, Consistency, and Monitorability
Microsoft claims Azure Storage providing both high availability and strong consistency. It sounds good but obviously violates the CAP theorem as the 'P' (network partitioning) is not avoidable in the real world. In theory, you can only achieve either high availability or strong consistency in a distributed storage system. I have done a bit of … Continue reading How Azure Storage Cheats Over the CAP Theorem
Data Ninjago (Financial Data Architecture) 
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