Presentations
43:42
In-Memory Caching: Curb Tail Latency with Pelikan
Yao Yue introduces Pelikan, a framework to implement distributed caches such as Memcached and Redis.
01:27:28
Microservices to FastData in the Enterprise with Spring
John T Davies is using Spring Integration and Spring Boot to ingest gigabytes of complex data into two different in-memory data grids (IMDGs), showing the design and implementation with several demos.
58:05
The Lightning Memory-mapped Database
Howard Chu discusses the Lightning Memory-Mapped Database (LMDB) design and architecture, and its impact on other projects such as OpenLDAP.
44:53
Ground-up Introduction to In-memory Data
Viktor Gamov covers In-Memory technology, distributed data topologies, making in-memory reliable, scalable and durable, when to use NoSQL, and techniques for Big In-Memory Data.
01:01:06
Web Clustering, Integration with Terracotta, BigMemory, Quartz & Grails
Ryan Vanderwerf speaks about the roles of cache clustering, session clustering, and quartz clustering with open source Terracotta, Quartz, and BigMemory.
39:12
An API for Distributed Computing
Cliff Click introduces a coding style & API for in-memory analytics that handles datasets from 1K to 1TB without changing a line of code and clusters with TB of RAM and hundreds of CPUs.
46:57
Equity – Transparent and Live Risk Assessment
Tormod Varhaugvik provides a design and rationale for an In Memory and Big Data architecture for live equity and risk assessment, using Tax Norway’ new architecture as an example.
55:39
In-Memory Message & Trade Repositories
John Davies walks through a reference implementation of a in-memory database meant to combine dozens of different legacy databases developed by banks over time.
Fighting the 21st Century Fraudster
Kunal Bhasin discusses in-memory and Big Data computing techniques used for the detection of banking fraud in real time.
