How to Process 50 Billion Monthly Messages with Full Availability & Performance

Yuan Ren, Head of Data Science, mParticle

Tue. Aug. 15, 2017 6:30pm   -   NYC
Free beer & drinks, junk food, swag and more!

Yuan Ren

Head of Data Science, mParticle

How to Process 50 Billion Monthly Messages with Full Availability & Performance

In this tech talk, Yuan Ren, Head of Data Science at mParticle, will show you how to design a high throughput and low latency NoSQL deployment.

In this fun-filled presentation you will learn:

  • How to stop worrying about mix workloads, read-modify-write, compaction and tuning
  • Why we switched from Apache Cassandra to ScyllaDB, an open source database that is fully compatible with Apache Cassandra
  • How to more effectively utilize high capacity Amazon Web Services (AWS) hardware, including the 64 vcpu, 15TB NVMe i3.16xl instances to run a 100TB dataset with just 10 nodes

mParticle captures more than $5 billion in e-commerce transactions over 1 billion monthly active users. Despite its challenging workload, with read-modify-write patterns on huge payload and strict read latency SLAs, mParticle achieves breakneck throughput and low latency without compromising on global database availability.

Yuan Ren

Head of Data Science,
mParticle

Yuan Ren is Head of Data Science at mParticle and works on building data driven products ranging from backend data pipeline to custom-facing analytics. Yuan has a background in software engineering and machine learning.

Previously, Yuan was the Senior Principal Research Engineer for Yahoo's interclick division. At Yahoo, Yuan built algorithms and services to optimize digital advertising performance.