How to Achieve 1M+ Record/Second Kafka Ingest without Sacrificing Query Latency

As our world moves towards being “always-on,” the ability to make decisions and predictions on streaming data in real-time has become mission-critical. Apache Kafka has paved the way for organizations to capitalize on the power of streaming data, but it needs supporting technology to enable real-time analytics.

Watch on demand to learn how FeatureBase and Kafka work together to achieve high throughput and low latency without sacrificing data freshness. Here’s what we’ll cover:

  1. How to ingest >1M records per second without sacrificing query latency
  2. How to rapidly update billions of records with real-time updates and inserts
  3. Learn to do automatic schema updates without manual changes or cutover downtime

Featured speakers

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Erica Fowler, PhD
Senior Product Marketing Manager

Erica is a strategy and analytics professional with 12 years of experience designing, implementing, and read more…

Garrett Raska - Lead Sales Engineer

Garrett Raska
Solutions Engineering Lead

Garrett is an engineering and sales professional with ten years of experience working with complex read more…

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