White Paper

Stream and Query in Real-Time

Kafka transformed event streaming by making it possible to move massive volumes of real-time data reliably between systems. But modern AI and event-driven applications require more than transport. Fraud detection, feature engineering, AI inference, personalization, and operational automation all depend on events being immediately available for processing, querying, and action the moment they arrive. Today, achieving that typically means adding stream processors, ETL pipelines, analytical stores, and query engines. Each layer adds latency, complexity, and additional copies of the same data. The next evolution in streaming is making events immediately actionable and immediately queryable at the same time.

Download the white paper to learn:

  • How VAST Event Broker makes every Kafka topic immediately queryable as a live database table with zero code changes to existing producers or consumers

  • Why VAST's Disaggregated Shared-Everything architecture eliminates broker-level replication and partition rebalancing while scaling compute independently of storage 

  • Benchmarked throughput results showing how VAST compares to Apache Kafka and Redpanda on equivalent hardware

  • How incoming JSON events get parsed into structured, SQL-queryable columns automatically, with no ETL pipeline or Spark job required

  • What migration actually looks like for Kafka environments, and how to evaluate a pilot in days rather than months

  • Real-world applications in fraud detection, real-time feature engineering, industrial telemetry, and operational observability

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