From Batch to Real-Time: How Production AI is Reshaping Data Architecture

As enterprises deploy AI systems into production, real-time data streaming has become an essential requirement rather than an optional feature. The traditional batch-processing approach creates unacceptable latency for AI systems that need to operate continuously and respond instantly to market changes. This architectural shift from static pipelines to 'data in motion' is forcing organizations to rethink their entire infrastructure strategy around Apache Kafka, Apache Flink, and real-time databases like Aerospike.