What We Talk About When We Talk About Real-Time

The concept of "real-time" is subjective and context-dependent, varying across industries and organizations. A real-time system is not just faster, but fast enough to cross a performance threshold where business can reproducibly gain net new value. Two classes of real-time applications exist: machines programmatically making data-driven decisions, such as digital advertising, and humans responding to events and making data-driven decisions in real time, like data center management. The definition of "real-time" is often heuristically defined, allowing stakeholders to establish conventions tailored to their business problems. Real-time systems must be able to process and analyze large amounts of data quickly, with the ability to extract actionable information from it being crucial. Enterprises are deploying real-time data pipelines that can ingest, serve, and query data simultaneously, using technologies like SingleStore, Apache Kafka, and Spark Streaming.

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