Sergey Tryuber

This article introduces the Grid Dynamics Blueprint for In-Stream Processing, which provides a pre-integrated, cloud-ready, and production-ready architecture for building scalable and fault-tolerant in-stream processing services using open source technologies such as Apache Kafka, Spark Streaming, Cassandra, and Redis.

This article provides a survey of different In-Stream Processing solutions on the market, focusing on critical architectural differentiations that may affect a customer’s decision to build or buy, rely on open source or a vendor, commit to a specific cloud or have portability, and use a blueprint or design from scratch.

In-Stream Processing is a technology that can analyze and act upon data in real-time, without stopping the data stream. It is used in various industries for applications such as fraud detection, recommendation engines, and dynamic pricing.