Skip to main content

GraphDatabase - The future for Facebook Recommendations

On what Basis are you getting Recommendations from Facebook??How your data is stored Internally in Social Network Sites ??

Have you ever thought how your information is stored by facebook in database?? Do you think its SQL that facebook is using for storing your data ?? If you think so ,then you are wrong.Its NoSQL GraphDatabase called 'Cassandra' what facebook uses to store your data.I know after reading this you will get lot of questions in your mind. 'What is Graph database??  How it looks like?? How it can be useful for Facebook Recommendations?? Where else it can be used??'.Let me explain each one in detail.

What is Graph database??

I think Wikipedia gives the best answer for this question.So i think i can just add a link to wikipedia for the introduction of graphDatabase. Here you go..!!

How it looks like??

I thing you got a basic idea about graph database after seeing Wikipedia page.Here i am showing sample example of a small Social Network of friends who KNOWS each other.



You can Imagine the entire Facebook database as a infinite Graph where the users keep on increasing day by day.Some thing like this
Where each node represents each Facebook user or  page and each edge between two users represents a FRIEND and LIKE relationship.

How it can be useful for Facebook Recommendations??

Consider the sample example of a small graph which has 3 users A,B,C.

  1. A - friend of B 
  2. B - friend of A,C 
  3. C - friend of B
 Now if u notice Facebook recommends 'C to A' and 'A to C ' to make friendship each other as 'user B' is the common friend between them.And this is as simple as to find the common node between two edges in GraphDatabase.

If you use SQL u need to join all 3 records together based on 'friends' field and need to find out the transitive relationship between A,B,C which is time taking.

The above example is a very basic one.More recommendations can be found out using mutual LIKES between two users,games,pages,etc...what not..!! These things can be easily implemented using GraphDatabase and it is very efficient than SQL.

Where else it can be used??

I feel GraphDatabases are very efficient to use for social networking,spatial search,recommendation engines(Ex: Amazon,Facebook),etc ....

Labels:

Comments

Post a Comment

Popular posts from this blog

How MongoDB survives From SQL or Query Injection

As We know SQL injection  is one of the most famous way people try to hack the SQL based applications.I came to know about interesting thing how  MongoDB  survives from this SQL injection while reading the mongodb docs. For SQL based applications most of the drivers support accessing SQL data using query as String which makes the access vulnerable. For Example in Java we use to get the data from SQL as follows, String query = "SELECT ZipCode,State FROM zipcodes WHERE City = '+city+' AND State = '+state+'"; connection = DriverManager.getConnection(jdbcurl, username, password); Statement stmt = connection.createStatement(); ResultSet rs = stmt.executeQuery(query); In case of MongoDB there is no vulnerability because all the drivers creates a BSON object for the given Query instead of calling the DB as a string itself. For MongoDb in Java QueryBuilder is used to build Queries for accesing MongoDb Data, DBObject query = QueryBu...
2 comments
Read more

Three Database Revolutions

There are three database revolutions that happened so far.   The first revolution was driven by the emergence of the electronic computer. The second revolution by the emergence of the relational database. The third revolution has resulted in an explosion of non-relational database alternatives driven by the demands of modern applications that require global scope and continuous availability. Lets have a look on these three waves of database technologies and discuss the market and technology forces leading to today’s next generation databases. 1950-1972 (Pre - Relational) 1951 - Magnetic Tape 1952 - Magnetic Disk 1961 - ISAM 1965 - Hierarchical Model 1968 - IMS 1969 - Network Model 1971 - IDMS 1972 - 2005 (Relational) 1970 - Codd's Paper 1974 - System R 1978 - Oracle 1980 - Commercial Ingres 1981 - Informix 1984 - DB2 1987 - Sybase 1989 - Postgres 1989 - SQL Server 1995 - MySQL 2005 - 2015 ( The Next Generation)  2003 - MarkLogic 2004 ...
Post a Comment
Read more

Why Nooooo SQL .........???

                       Relational databases have been around for many decades and are the database technology of choice for most traditional data-intensive storage and retrieval applications. Retrievals are usually accomplished using SQL, a declarative query language. Relational database systems are generally efficient unless the data contains many relationships requiring joins of large tables. Recently there has been much interest in data stores that do not use SQL exclusively, the so called NoSQL movement. Examples are Google’s BigTable and Facebook’s Cassandra . Lets have a look at NoSQL  vs  MySQL (common relational database system).   When to go for  NOSQL ?? In recent years, software developers have been investigating storage alternatives to relational databases. NoSQL is a blanket term for some of those new systems. Cassandra,BigTable, CouchDB, Project Voldemort, and Dynamo are all...
Post a Comment
Read more