Scalability in distributed in-memory systems
Platforms for distributed in-memory computing such as Apache Ignite rely on horizontal scaling. The bigger the cluster is, the bigger profit you get. Does adding a second machine double the performance? Does adding ten more give you and order of magnitude change? Is it always this way? What is the responsibility of a framework, and what is responsilbility of a developer?
In this talk we'll examine the most important compromises and contradictions that arise while designing applications with the in-memory systems:
- Pros and cons of different sharding techniques
- Data model adaptation for effective work in a cluster
- Problems of synchronization and coordination in distributed systems
Yakov Zhdanov
Yakov started working at GridGain in 2010. He currently leads the Russian branch of the company, being involved in the development process and making of technical decisions. Commits to Apache Ignite. Can't imagine summer without bikes or winter without snow and mountains.