์‹ค์‹œ๊ฐ„ ์›€์ง์ด๋Š” ๋ฐ์ดํ„ฐ๊ฐ€ ๊ฐ€์ ธ๋‹ค ์ค„ ๊ฐ€์น˜, Data in Motion Tour์—์„œ ํ™•์ธํ•˜์„ธ์š”!

Supercharge Your Real-time Event Processing with Neo4j's Streams Kafka Connector

Do your event streams use connected-data domains such as fraud detection, live logistics routing, or predicting network outages? How can you maintain the analysis and leverage those connections real-time?

Graph databases differ from traditional, tabular ones in that they treat connections between data as first class citizens. This means they are optimized for detecting and understanding these relationships โ€“ providing insight at speed and at scale.

By combining event streams from Kafka along with the power of the Neo4j graph database for interrogating and investigating connections, you make real-time, event-driven intelligent insight a reality.

Neo4j Streams integrates Neo4j with Apache Kafka event streams, to serve as a source of data, for instance Change Data Capture or a sink to ingest any kind of Kafka event into your graph. In this session weโ€™ll show you how to get up and running with Neo4j Streams to show you how to sink and source between graphs and streams.

Chinese Japanese Korean

๋ฐœํ‘œ์ž

Ljubica Lazarevic