Caching
Scalability Perspectives is a series of posts that highlights the ideas that will shape the next decade of IT architecture. Each post is dedicated to a thought leader of the information age and his vision of the future. Be warned though – the journey into the minds and perspectives of these
Paper
Abstract—This paper presents the architecture and characteristics of a memory database intended to be used as a cache engine for web applications. Primary goals of this database are speed and efficiency while running on SMP systems with several CPU cores (four and more). A secondary goal is the support
Grid
During the Coherence Special Interest Group meeting in London, Brian Oliver from Oracle yesterday announced the start of the Coherence Incubator project. Coherence Incubator is a new online repository of projects that provides reference implementation examples for commonly used design patterns and integration solutions based on Oracle Coherence.
Product
ScaleOut StateServer is an in-memory distributed cache across a server farm or compute grid. Unlike middleware vendors, StateServer is aims at being a very good data cache, it doesn't try to handle job scheduling as well. StateServer is what you might get when you take Memcached and merge
Strategy
Pre-generating static files is an oldy but a goody, and as Thomas Brox Røst says, it's probably an underused strategy today. At one time this was the dominate technique for structuring a web site. Then the age of dynamic web sites arrived and we spent all our time
Java
Update:Evaluating Terracotta by Piotr Woloszyn. Nice writeup that covers resilience, failover, DB persistence, Distributed caching implementation, OS/Platform restrictions, Ease of implementation, Hardware requirements, Performance, Support package, Code stability, partitioning, Transactional, Replication and consistency. Terracotta is Network Attached Memory (NAM) for Java VMs. It provides up to a terabyte
Product
Ehcache is a pure Java cache with the following features: fast, simple, small foot print, minimal dependencies, provides memory and disk stores for scalability into gigabytes, scalable to hundreds of caches is a pluggable cache for Hibernate, tuned for high concurrent load on large multi-cpu servers, provides LRU, LFU and
Scalability
Scalability forces us to think differently. What worked on a small scale doesn't always work on a large scale -- and costs are no different. If 90% of our application is free of contention, and only 10% is spent on a shared resources, we will need to grow
Database
This post covers two main options for scaling-out MySql and compare between them. The first is based on data-base clustering and the second is based on In Memory clustering a.k.a Data Grid. A special emphasis is given to a pattern which shows how to scale our existing data
Database
[Tim O'Reilly] Continuing my series of queries about how "Web 2.0" companies used databases, I asked Cal Henderson of Flickr to tell me "how the folksonomy model intersects with the traditional database. How do you manage a tag cloud?"
Oracle
One of the most interesting new features of Oracle 11 is the new function result caching mechanism. Until now, making sure that a PL/SQL function gets executed only as many times as necessary was a black art. The new caching system makes that quite easy -- here is how
IIS
Effective content caching is one of the key features of scalable web sites. Although there are several out-of-the-box options for caching with modern web technologies, a custom built cache still provides the best performance.