The Drizzle Project is a fork of the MySQL 6.0 server, aimed at serving large cloud computing environments. One of the many goals of Drizzle is to enable a large plugin ecosystem by improving, simplifying, and modernizing the application programming interfaces between the kernel and the modules providing services for Drizzle.
Drizzle’s replication system is entirely new and different from MySQL. It uses Google Protobuffer messaging in its application programming interface to communicate changes to the state of one server to another server. Plugins are easy to implement which enable a developer to entirely customize their replication system. This tutorial describes the APIs used in Drizzle’s replication system in depth and walks through the construction of several example plugins demonstrating the flexibility and power of the replication API.
Topics covered include:
by Mike Dirolf
MongoDB is an open-source, high-performance, schema-free, document-oriented database. The goal of the MongoDB project is to bridge the functionality gap between a key/value store and a traditional RDBMS. This talk will introduce MongoDB and discuss some of the reasons why MongoDB might be the right fit for your project.
We'll introduce MongoDB by explaining how it compares to traditional relational databases as well as some other non-relational systems. This will focus on the gains in scalability and flexiblity that make MongoDB an attractive option, as well as some examples of when MongoDB might not be the best fit. Following this introduction we will discuss some specific use cases for MongoDB. This will include examples of interacting with MongoDB from several different languages. We will review some of the advanced features of MongoDB and discuss how they can be put to good use.
Questions and discussion will be encouraged throughout the presentation. We'll be able to dive deeper into any specific topics of interest to the audience.
Cassandra is an open source, highly scalable distributed database that's rapidly gaining momentum in the NoSQL community. It brings together Dynamo's fully distributed design and Bigtable's ColumnFamily-based data model to provide a unique data storage solution that is suitable to a wide variety of use cases.
Professor Eric Brewer's CAP theorem states that a distributed system design can offer at most two out of three desirable properties: Consistency, Availability, and Partition Tolerance. So, how do you provide consistency when your distributed system's primary requirements are availability and partition tolerance?
In this talk we'll introduce eventual consistency and the four strategies that Cassandra uses to provide it, while still maintaining high availability:
* Gossip
* Read Repair
* Hinted Hand-off
* Anti-Entropy