NoSQL Databases: Cassandra and MongoDB

Cassandra

Cassandra is a free post-relational database solution with characteristics:

• distributed
• high performance (flexible partitioning ,replica placement)
• extremely/ linearly scalable and
• fault tolerant (no single point of failure)
• flexible schema design
• data compression
• cql (like SQL)
• data consistency
• no need of separate caching layer and special h/w or s/w

Cassandra can serve as both real-time data store for online/transactional apps or intensive database for business intelligence systems. It is used as backend storage system for multiple services in facebook.

Cassandra is a love child of Google's BigTable and Amazon's Dynamo. Netflix, twitter, cisco etc are among the Cassandra users.

Data Model

• Cassandra is a distributed key-value store.
• A table in Cassandra is a distributed multi-dimensional map indexed by a key. The value is an object which is highly structured.
• The row key in a table is a string with no size restrictions, although typically 16 to 36 bytes long.
• Every operation under a single row key is atomic per replica no matter how many columns are being read or written into.
• The columns are grouped together into sets called column families.
• Cassandra exposes its two kinds of columns families, Simple and Super column families. [2]
• Super column families(meta) can be visualized as a column family within a column family.

The Cassandra API consists of the following three simple methods.

• get(table; key; colName)
• insert(table; key; rowMutation)
• delete(table; key; colName)

colName can refer to a specific column within a column family, a column family, a super column family, or a column within a super column.[1]

Architecture

• System is fault tolerant, as it was designed considering system/hardware failure can and do occur
• Is p2p, distributed system.
• All nodes the same and data partitioned with all nodes in a cluster.[3]
• Custom data replication to ensure fault tolerance.
• Read/Write -anywhere design
• Each node communicates with each other through the Gossip protocol, which exchanges information across the cluster every second
• A commit log is used on each node to capture write activity. Data durability is assured
• Data also are written to an in-memory structure (memorable) and then to disk once the memory structure is full (an SStable)
• Schema used in Cassandra is mirrored after Google BigTable. It's a row-oriented, column structure
• A keyspace is akin to a database in the RDBMS world
• A column family is similar to an RDBMS table but is more flexible/dynamic
• A row in a column family is indexed by its key. Other columns may be indexed as well Portfolio Keyspace Customer Column Family ID Name SSN DOB

MongoDB

• 10gen began dev in 2007 and initial release in 2009
• Open-source
• cross-platform
• written in c++
• document oriented DB
• high performance and availability
• work on the concept of collection and document

• Master/slave replication (auto-failover with replica sets)
• Sharding built-in
• Queries are javascript expressions
• Run arbitrary javascript functions server-side
• Uses memory mapped files for data storage
• An empty database takes up 192Mb
• GridFS to store big data + metadata (not actually an FS)

Features

• Ad hoc queries: supports field, regular expression or queries that return a random sample result of a given size.
• Indexing
• Replication
• Load balancing: data in a collection is distributed (split) based on shard key (shard is master with 1 or many slaves)
• File storage : can be used as Grid File System.
• Aggregation : can be used mapReduce for batch processing or aggregation operations
• Server-side JavaScript execution
• Capped collections: fixed size collection to maintain the insertion order [4]

Data model

• Data model: Using BSON (binary JSON), developers can easily map to modern object-oriented languages without a complicated ORM layer.
• BSON is a binary format in which zero or more key/value pairs are stored as a single entity.
• is lightweight, traversable, efficient.

Advantages of MongoDB over RDBMS

• Structure of a single object is clear
• No complex joins
• Deep query-ability : supports dynamic queries on documents using a document-based query language that's nearly as powerful as SQL
• Schema-less : document database in which a collection may hold different documents. A number of fields, content, and size of the document can differ from 1 document to another.
• Tuning
• Ease of scale-out : easy to scale
• Conversion / mapping of application objects to database objects not needed
• Uses internal memory for storing the (windowed) working set, enabling faster access of data

Some basic commands in MongoDb

1.To use MongoDB

->mongo

2.MongoDB Help

->db.help()

3.MOngoDB Statistics

->db.stats()

4.TO create Database

->use Database_name

switched to Database_name

5.Check Database lists

->show dbs

6.Drop database

->db.dropDatabase()

7.Create Collection

->db.createCollection(name, options)

where, name= name of collection

options= options about memory size and indexing

//in MongoDB no need to specify the options

8.Drop Collection

->db.COLLECTION_NAME.drop()

9.Insert Document

->db.COLLECTION_NAME.insert(document)

Example:

db.user.insert({user_name:"Raju",Age:"21",Address:"Pokhara"})

//WriteResult({ "nInserted" : 1 })

10.To query data from MongoDB

->db.user.find().pretty() //user = collection

{

"_id" : ObjectId("55e43a8cf585cca56cafc325"),

"user_name" : "Raju",

"Age" : "21",

"Address" : "Pokhara"

}

11.Update Data in MongoDB

->db.user.update({'user_name':"Raju"},{$set:{"user_name":"Manoj"}},{multi:true})

->db.user.find().pretty()

{

"_id" : ObjectId("55e43a8cf585cca56cafc325"),

"user_name" : "Manoj",

"Age" : "21",

"Address" : "Syangja"

}

12. Remove document in MOngoDB

->db.user.remove({'user_name':"Manoj"}) //Delete only one column

->db.user.remove() //same as truncate in RDBMS

References:

1. "Cassandra - A Decentralized Structured Storage System", Avinash Lakshman,Prashant Malik
2. "Big Data and Internet of Things: A Roadmap for Smart Environments", Nik Bessis, Ciprian Dobre, page 77
3. "Architecture in brief" at doc.datastax.com
4. "Databases and Collections" at doc.mongodb.com