Tag: Database
"Scale breaks everything. Scale even breaks your assumptions about how best to store and query data. Scale does not care about your personal engineering preferences, or about SQL vs. NoSQL."
How to isolate customer's data from one another (one database per customer).
This document showcases many of the latest developments in PostgreSQL 9.0, compared to the last major release - PostgreSQL 8.4. There are more than 200 improvements in this release. While all the important advances are explained and demonstrated, some of the more esoteric changes are not covered, but these are unlikely to be known issues for most users.
Presentation by Nice Alex Gaynor (Berlin, Germany).
"The Django ORM is pretty complicated and it takes too much time for contributors to understand all the necessary details. In order to make the process as easy as possible we've implemented a backend template which provides a simple starting point for a new backend based on our simplified API. It also contains sample code, so you can better understand what each function does." by All buttons pressed
"All listed tools are relatively easy to get running, so I encourage you to play with them to see which one you like the best" via Tim's Daft Jun
"There are so many NoSQL systems these days that it's hard to get a quick overview of the major trade-offs involved when evaluating relational and non-relational systems in non-single-server environments" via Nathan Hurst’s Blog
MongoEngine is a Document-Object Mapper for working with MongoDB from Python. It uses a simple declarative API, similar to that of the Django ORM
Because SQL databases proved to be such an excellent tool within this narrow but often useful role, developers found themselves reaching for the SQL database for any job at all. It’s the default, the catch-all for storing nearly anything the application developer can think of - and even some things that aren’t data storage at all. When all you have is a hammer, etc.
Werner Vogels (Amazon CTO) wrote " Keeping your database simple and fast is often difficult if you use higher level frameworks such as ActiveRecords in Ruby or Java object persistence technologies such as Hibernate. There is a lot of magic that is happening out of sight that you have no control over.".
Jurriaan Persyn wrote how to handle 5 billions page views per month using MySQL sharding.
Bret Taylor wrote in his blog how FriendFeed uses MySQL to store schema-less data.
Tokyo Cabinet Python bindings
Tokyo Cabinet is a library of routines for managing a database. The database is a simple data file containing records, each is a pair of a key and a value. Every key and value is serial bytes with variable length. Both binary data and character string can be used as a key and a value. There is neither concept of data tables nor data types. Records are organized in hash table, B+ tree, or fixed-length array.
Tony Bain wrote "Recently, a lot of new non-relational databases have cropped up both inside and outside the cloud. One key message this sends is, "if you want vast, on-demand scalability, you need a non-relational database". If that is true, then is this a sign that the once mighty relational database finally has a chink in its armor? Is this a sign that relational databases have had their day and will decline over time?"