high_scalability high_scalability-2009 high_scalability-2009-538 knowledge-graph by maker-knowledge-mining
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Introduction: We are on the edge of two potent technological changes: Clouds and Memory Based Architectures. This evolution will rip open a chasm where new players can enter and prosper. Google is the master of disk. You can't beat them at a game they perfected. Disk based databases like SimpleDB and BigTable are complicated beasts, typical last gasp products of any aging technology before a change. The next era is the age of Memory and Cloud which will allow for new players to succeed. The tipping point will be soon. Let's take a short trip down web architecture lane: It's 1993: Yahoo runs on FreeBSD, Apache, Perl scripts and a SQL database It's 1995: Scale-up the database. It's 1998: LAMP It's 1999: Stateless + Load Balanced + Database + SAN It's 2001: In-memory data-grid. It's 2003: Add a caching layer. It's 2004: Add scale-out and partitioning. It's 2005: Add asynchronous job scheduling and maybe a distributed file system. It's 2007: Move it all into the cloud. It's 2008: C
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1 Why might cloud based memory architectures be the next big thing? [sent-20, score-0.735]
2 For now we'll just address the memory based architecture part of the question, the cloud component is covered a little later. [sent-21, score-0.566]
3 Memory is the System of Record What makes Memory Based Architectures different from traditional architectures is that memory is the system of record . [sent-33, score-0.491]
4 The purpose behind cache based architectures is to minimize the data bottleneck through to disk. [sent-41, score-0.472]
5 The dramatic drop of RAM prices along with the ability of servers to handle larger and larger amounts of RAM has caused memory architectures to verge on going mainstream. [sent-45, score-0.426]
6 As an architecture it combines the holy quadrinity of computing: Performance is better because data is accessed from memory instead of through a database to a disk. [sent-61, score-0.522]
7 Reading data from memory is also faster than reading data from disk. [sent-68, score-0.499]
8 Terracotta - Terracotta is network-attached memory that allows you share memory and do anything across a cluster. [sent-104, score-0.514]
9 Operates as an in-memory data grid that dynamically caches, partitions, replicates, and manages application data and business logic across multiple servers. [sent-108, score-0.416]
10 And there are other architectures that will exploit memory yet won't be classic IDMG. [sent-112, score-0.426]
11 But the speed of memory versus disk also allows entire new levels of performance and reliability in a relatively simple and easy to understand and deploy package. [sent-130, score-0.485]
12 I've probably said this before, but the cloud is a new computing platform that some have learned to exploit, others are scrambling to master, but most people will see as nothing but a minor variation on what they're already doing. [sent-140, score-0.414]
13 When departmental computing came along (VAXes, et al), the timesharing guys considered it nothing but timesharing on a smaller scale. [sent-143, score-0.494]
14 When PCs and client/server computing came along, the departmental computing guys (i. [sent-144, score-0.408]
15 So the batchguys are dead, the timesharing guys are dead, the departmental computing guys are dead, and the client server guys are dead. [sent-148, score-0.668]
16 The reason that databases are important to cloud computing is that virtually all applications involve the interaction of client data with a shared, persistent data store. [sent-150, score-0.65]
17 What I'm arguing is that a cloud is a different platform, and what works well for a single computer doesn't work at all well in cloud, and things that work well in a cloud don't work at all on the single computer system. [sent-159, score-0.638]
18 The alternative is to use the memory in a cloud as a distributed L2 cache. [sent-165, score-0.444]
19 The network serves everyone in parallel while the disk is single threaded I favor data sharing through a formal abstraction like a relational database. [sent-173, score-0.559]
20 Jim certainly isn't shy with his opinions :-) My summary of what he wants to do with NimbusDB is: Make a scalable relational database in the cloud where you can use normal everyday SQL to perform summary functions, define referential integrity, and all that other good stuff. [sent-244, score-0.416]
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