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NoSQL Style (Gangnam Style Parody for Geeks) UC Berkeley Course Lectures: Analyzing Big Data With Twitter. Thank you all for a wonderful semester.

UC Berkeley Course Lectures: Analyzing Big Data With Twitter

Here is a summary, in chronological order, of our recorded lectures. You can also view the entire playlist on youtube. Course Introduction Marti Hearst, the course instructor at UC Berkeley, introduces the main concepts for the course, and Gilad Mishne (@gilad) of Twitter describes his goals for the course and provides an introduction to Twitter. The State of NoSQL in 2012. This is a guest post by Siddharth Anand, a senior member of LinkedIn's Distributed Data Systems team.

The State of NoSQL in 2012

Preamble Ramble If you’ve been working in the online (e.g. internet) space over the past 3 years, you are no stranger to terms like “the cloud” and “NoSQL”. In 2007, Amazon published a paper on Dynamo. The paper detailed how Dynamo, employing a collection of techniques to solve several problems in fault-tolerance, provided a resilient solution to the on-line shopping cart problem. The Coming SQL Collapse. I looked at neo4j briefly the other day, and quite predictably thought ‘wow, this looks like a serious tinkertoy: it‘s basically a bunch of nodes where you just blob your attributes.‘ Worse than that, to wrap objects around it, you have to have them explicitly incorporate their node class, which is ugly, smelly, violates every law of separation of concerns and logical vs. physical models.

The Coming SQL Collapse

Choosing a non-relational database; why we migrated from MySQL to MongoDB « Boxed Ice Blog.


HBase - HBase Home. Hypertable: An Open Source, High Performance, Scalable Database. Leveling the Field. July 1, 2011.

Leveling the Field

Cassandra vs MongoDB vs CouchDB vs Redis vs Riak vs HBase comparison. (Yes it's a long title, since people kept asking me to write about this and that too :) I do when it has a point.)

Cassandra vs MongoDB vs CouchDB vs Redis vs Riak vs HBase comparison

While SQL databases are insanely useful tools, their monopoly in the last decades is coming to an end. And it's just time: I can't even count the things that were forced into relational databases, but never really fitted them. (That being said, relational databases will always be the best for the stuff that has relations.) But, the differences between NoSQL databases are much bigger than ever was between one SQL database and another.

Introduction to Redis - In Memory Key Value Datastore. We Recommend These Resources I have been thinking about taking a deep dive into NoSQL databases for a long time but wasn't sure which one should I start with.

Introduction to Redis - In Memory Key Value Datastore

There are a lot of NoSQL databases in the market, each solving a set of problems. I wanted to learn a NoSQL database that does not have a steep learning curve and is generic enough to solve more than one problem. So, I started looking into different NoSQL databases when I found my starting point: Redis. S tech blog » Why startups should not choose NoSQL. December 27, 2010 The NoSQL hype is omnipresent.

s tech blog » Why startups should not choose NoSQL

And many startups are tempted to go for Cassandra/MongoDB/HBase/Redis/… . Here I’ll argue why they should rather stick to a SQL solution – MySQL or PostgreSQL. Babudb - Project Hosting on Google Code. BabuDB is an embedded non-relational database system.

babudb - Project Hosting on Google Code

Its lean and simple design allows it to persistently store large amounts of key-value pairs without the overhead and complexity of similar approaches such as BerkeleyDB. Key features: Support for large-scale databases that exceed the system's main memory Efficient crash recovery Snapshots and asynchronous dumps Prefix and range lookups Transparent replication with tuneable consistency/performance trade-offs BabuDB has been independently implemented for Java and C++ (Win32/Linux). APIs and database formats of both implementations are not compatible. Banana DB - self-contained key/value pair database for java. Banana DB Banana DB is a self-contained key/value pair database implemented in Java.

Banana DB - self-contained key/value pair database for java

Features Small, ~100KB .jar file with no dependencies.Top level API similar to working with any Map<K, V> on to of core <byte[], byte[]> index.Thread safe and write locking over multiple JVMs using extended Lucene locks.Optionally transactional.More or less ACID -compliant.Simple annotational API.Pluggable serialization strategies. ( as default) Upcoming features Optimized generic serialization.Secondary indices.

Non-RDBM distributed databases, map/reduce, key/value and cloud computing. I've been playing recently with several distributed databases with the aim of choosing the best solution for my needs.

non-RDBM distributed databases, map/reduce, key/value and cloud computing

Since there isn't much documentation on the web with a general overview on the subject, I write here some comments, thoughts and my humble experience. Hope it's usefull for you, this document is not a comparison of performance, or a "mine is bigger than yours", just some ideas ;) My background Being my experience based on relational databases (like MySQL or Postgres) and Object oriented databases (like ZODB) it was very easy for me to get hooked on this new challenge, anything but the relational databases (no offense).

Last year, in Mainz, Germany, and after having heard a lot of buzz on the subject, Jan Lehnardt gave an interesting lecture on CouchDB. (BTW, thanks Jan for all the questions you answered to me). Anti-RDBMS: A list of distributed key-value stores. Written on 19 January 2009 Please Note: this was written January 2009 - see the comments for updates and additional information. Troubles with Sharding - What can we learn from the Foursquare Incident? For everything given something seems to be taken. Caching is a great scalability solution, but caching also comes with problems. Sharding is a great scalability solution, but as Foursquare recently revealed in a post-mortem about their 17 hours of downtime, sharding also has problems. MongoDB, the database Foursquare uses, also contributed their post-mortem of what went wrong too.

Now that everyone has shared and resharded, what can we learn to help us skip these mistakes and quickly move on to a different set of mistakes? First, like for Facebook, huge props to Foursquare and MongoDB for being upfront and honest about their problems. Second, overall, the fault didn't flow from evil hearts or gross negligence. Was it preventable? NOSQL Databases. NoSQL/Home Page.

A Relational Database Management System NoSQL is a fast, portable, relational database management system without arbitrary limits, (other than memory and processor speed) that runs under, and interacts with, the UNIX1 Operating System. It uses the "Operator-Stream Paradigm" described in "Unix Review", March, 1991, page 24, entitled "A 4GL Language". There are a number of "operators" that each perform a unique function on the data. The "stream" is supplied by the UNIX Input/Output redirection mechanism. Therefore each operator processes some data and then passes it along to the next operator via the UNIX pipe function. A Lightweight SQL Database for Cloud and Web in Launchpad.

Log in / Register A Lightweight SQL Database for Cloud Infrastructure and Web Applications. No to SQL? Anti-database movement gains stea. Eric Lai published a provoking article on Computerworld magazine titled “No to SQL? Anti-database movement gains steam” where he pointed to many references in which different Internet-based companies chose an alternative approach to the traditional SQL database.

The write-up was driven from the the inaugural get-together of the burgeoning NoSQL community who seem to represent a growing Anti-SQL database movement. Quoting Jon Travis from this article: Relational databases give you too much. They force you to twist your object data to fit a RDBMS [relational database management system], The article points to specific examples that led different companies such as Google, Amazon, Facebook to choose an alternative approach.

Demand for extremely large scale: “BigTable, is used by local search engine Zvents Inc. to write 1 billion cells of data per day.” Complexity and cost of setting up database clusters: Most Trendy Graph Databases. We Recommend These Resources The last two years of my working life I been at the UPC , specifically with the DAMA-UPC research group: the data management experts of this university. One of the lines of research is graph databases, which is the main topic of this post. In the same way that relational databases organize data in the form of tables, graph databases do this in the form of a graph, or a network. Nodes, edges, attributes and algorithms are the objects of interest in this field. NoSQL Graph Database Comparison. A few days ago I published a short overview of the most trendy graph databases. Today I'm bringing you a review of the most important features of them.