1、Data Observability&Reliability Engineering:Real-Time Imperative,Real-time data is now essential for competitive advantage in todays fast-paced business environment.,Organizations face unprecedented challenges with velocity,volume,variety,and veracity of data flowing through their systems.,Robust dat
2、a observability and reliability engineering practices have become critical for success.,NC,by Nilanjan Chatterjee,Reference Data Architecture,Data Pipeline Architectures:Lambda vs Kappa vs Delta,Lambda Architecture,Dual-processing approach combining batch and stream processing.,Batch layer for histo
3、rical data,Speed layer for real-time processing,Serving layer merges both views,Best for complex analytics requiring historical context.,Kappa Architecture,Stream-first approach treating all data as streams.,Single processing pathway,Log-based immutable data storage,Simplified maintenance,Ideal for
4、real-time systems with lower complexity requirements.,Delta Architecture,Modern evolution combining best aspects of both approaches.,ACID transactions,Schema enforcement,Time travel capabilities,Optimal for data reliability with real-time and historical needs.,Lambda Architecture,Dual-processing app
5、roach combining batch and stream processing.,Batch layer for historical data,Speed layer for real-time processing,Serving layer merges both views,Best for complex analytics requiring historical context.,Kappa Architecture:A Stream-First Approach,Stream-processing centric data pipeline design,Single
6、stream processing layer,Immutable event logs,Reprocessing capability,Best for complex real-time analytics requiring historical context.Uber uses a Kappa-like approach to process ride events in real time,then reprocesses data for billing adjustments,For details:https:/,Delta Architecture:A Medallion