This article describes a temporal data lake architecture for financial services that processes benchmark and indices analytics at scale using AWS services.

• Kinesis Data Streams ingests high-volume financial data in real-time JSON format
• Kinesis Data Analytics with Apache Flink performs bi-temporal calculations using RocksDB state management
• Apache Iceberg on S3 stores immutable time-series data with ACID compliance and schema evolution
• EventBridge and Lambda automatically scale cluster capacity before, during, and after peak loads
• Architecture processes 150 million records in under 5 minutes with 15-minute end-to-end SLA
• Append operations outperform Upsert operations in both speed and compute resource consumption
• Trino queries Apache Iceberg tables for SQL-like data access and analysis

The solution enables financial institutions to handle burst workloads while maintaining strict SLAs and reducing total cost of ownership through intelligent auto-scaling and efficient data processing patterns.