Growing Resilience in a Hyperscaled Financial Platform
summary
Describes scaling a financial platform from 66 million to over 25 billion records while preserving numeric accuracy and low latency. Covers pragmatic strategies for balancing high precision and low latency, optimizing application logic, and avoiding common database-scaling pitfalls rather than deep internals—aimed at engineers and system architects.
AI-written summary · about
chapters (14)
- 0:00Introduction
- 3:18Financial database role
- 5:53Relational DB scaling challenges
- 9:31Database scaling pyramid
- 10:15Base DB setup optimization
- 14:47Indexing importance
- 18:19App optimization and caching
- 21:33Query optimization
- 24:01Workload separation
- 27:39Data modernization
- 29:27Large table partitioning
- 31:16Data archiving
- 33:02Horizontal DB scaling
- 34:30Summary
related talks
38mScaling in 2012
15mArchitecting Scalable Platforms for Financial Wellness
18mScaling Without Limits: KFIN's Journey to Distributed SQL
32mBeyond Optimization: Resilient Cloud Microservices at Scale
10mBuilding High-Performance Financial Data Pipelines
41mThe Reality of Managing 100+ Managed Databases
30mModernizing Databases for Financial Services Applications
15mPlatform Engineering for FinTech