Making Sense of Stream Processing

techinnews September 28, 2017
Updated 2022/04/14 at 11:00 AM
making sense of stream processing
making sense of stream processing

Application development is fairly easy if a single monolithic data‐base can satisfy all of your requirements for data storage, access, and processing. As soon as that is no longer the case—perhaps due to scale, or complexity of data access patterns, or other reasons—there is a lack of guidance and patterns to help application developers build reliable, scalable and maintainable applications.

In this report, you will explore a particular architectural style for building large-scale applications, based on streams of immutable events (event logs). Stream processing is already widely used for analytics and monitoring purposes (e.g., finding certain patterns of events for fraud detection purposes, or alerting about anomalies in time series data), but in this report we saw that stream processing is also good for situations that are traditionally considered to be in the realm of OLTP databases: maintaining indexes and materialized views.

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