For Data Engineers

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 this webinar 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

**Note: This webinar was recorded before we rebranded from Molecula to FeatureBase!