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Getting started with couchdb

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NoSQL Definition

  • From www.nosql-database.org:
    • Next Generation Databases mostly addressing some of the points: being non-relational, distributed, open-source and horizontal scalable. The original intention has been modern web-scale databases.
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    • The movement began early 2009 and is growing rapidly. Often more characteristics apply as:
      • schema-free,
      • easy replication support,
      • simple API,
      • eventually consistent / BASE (not ACID),
      • a huge data amount, and more.
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    NoSQL Products/Projects

    http://www.nosql-database.org/ lists 122 NoSQL Databases
    • Cassandra
    • CouchDB
    • Hadoop & Hbase
    • MongoDB
    • StupidDB
    • Etc.
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    NoSQL Distinguishing Characteristics

  • Stands for Not Only SQL
  • Class of non-relational data storage systems
  • Usually do not require a fixed table schema nor do they use the concept of joins
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  • All NoSQL offerings relax one or more of the ACID properties (will talk about the CAP theorem)
  • Large data volumes
    • Google’s “big data”
  • Scalable replication and distribution
    • Potentially thousands of machines
    • Potentially distributed around the world
  • Queries need to return answers quickly
  • Mostly query, few updates
  • Open source development
  • Asynchronous Inserts & Updates
  • Schema-less
  • ACID transaction properties are not needed – BASE
  • CAP Theorem
    • Consistency
      • “is equivalent to requiring requests of the distributed shared memory to act as if they were executing on a single node, responding to operations one at a time.”
      • Not the same as “ACID”
      • Linearizability ~ operations behave as if there were no concurrency. Does not mention transactions
      • When no updates occur for a long period of time, eventually all updates will propagate through the system and all the nodes will be consistent
      • For a given accepted update and a given node, eventually either the update reaches the node or the node is removed from service
      • Known as BASE (Basically Available, Soft state, Eventual consistency), as opposed to ACID
        • Soft state – copies of a data item may be inconsistent
        • Eventually Consistent – copies becomes consistent at some later time if there are no more updates to that data item
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    • Available
      • “every request received by a non-failing node in the system must result in a response.”
      • says nothing about the content of the response. It could be anything; it need not be “successful” or “correct”.
    • Partition Tolerant
      • any guarantee of consistency or availability is still guaranteed even if there is a partition.
      • if a system is not partition-tolerant, that means that if the network can lose messages or any nodes can fail, then any guarantee of atomicity or consistency is voided.

    Typical NoSQL API

  • Basic API access:
    • get(key) -- Extract the value given a key
    • put(key, value) -- Create or update the value given its key
    • delete(key) -- Remove the key and its associated value
    • execute(key, operation, parameters) -- Invoke an operation to the value (given its key) which is a special data structure (e.g. List, Set, Map .... etc).

    Types of NoSQL datastores

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  • Key - value stores
    • Hash tables of Keys
    • Values stored with Keys
    • Fast access to small data values
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    • Example – Project-Voldemort
    • Example – MemCacheDB
    • Memcache ( just merged with CouchDB)
    • Redis
    • Riak
      • Pros:
        • very fast
        • very scalable
        • simple model
        • able to distribute horizontally
      • Cons:
        • - many data structures (objects) can't be easily modeled as key value pairs
  • Map Reduce in CouchDB
    • Technique for indexing and searching large data volumes
    • Two Phases, Map and Reduce
    • Map
      • Extract sets of Key-Value pairs from underlying data
      • Potentially in Parallel on multiple machines
    • Reduce
      • Merge and sort sets of Key-Value pairs
      • Results may be useful for other searches
    • Map Reduce techniques differ across products
    • Implemented by application developers, not by underlying software
  • Column stores
    • Big Table ( Google )
    • Dynamo
    • Hadoop/HBase
    • Cassandra
      • Originally developed at Facebook
      • Follows the BigTable data model: column-oriented
      • Uses the Dynamo Eventual Consistency model
      • Written in Java
      • Open-sourced and exists within the Apache family
      • Uses Apache Thrift as it’s API
        • Thrift - Created at Facebook along with Cassandra
        • Thrift - Is a cross-language, service-generation framework
        • Thrift - Binary Protocol (like Google Protocol Buffers)
        • Thrift - Compiles to: C++, Java, PHP, Ruby, Erlang, Perl, ...
    • Column Store - More Details - More efficient than row (or document) store if:
      • Multiple row/record/documents are inserted at the same time so updates of column blocks can be aggregated
      • Retrievals access only some of the columns in a row/record/document
  • Document stores
    • Couch DB
    • Mongo
    • JSON – JavaScript Object Notation
    • CouchDB JSON Example
      {
        "_id": "guid goes here",
        "_rev": "314159",
      
        "type": "abstract",
        
        "author": "Keith W. Hare"
      
        "title": "SQL Standard and NoSQL Databases",
      
        "body": "NoSQL databases (either no-SQL or Not Only SQL) 
                 are currently a hot topic in some parts of
                 computing.",
        "creation_timestamp": "2011/05/10 13:30:00 +0004"
      }
      Clicking "Copy Code" button will copy the code into the clipboard - memory. Please paste(Ctrl+V) it in your destination. The code will get pasted. Happy coding from Wikitechy couchdbs tutorial team
    • "_id"
      • GUID – Global Unique Identifier
      • Passed in or generated by CouchDB
    • "_rev"
      • Revision number
      • Versioning mechanism
    • "type", "author", "title", etc.
      • Arbitrary tags
      • Schema-less
      • Could be validated after the fact by user-written routine
  • Graph, Object Stores
    • Neo4J
    • db4o

    Couch DB

  • An Apache project create by….Damien Katz…
  • A document database server, accessible via a RESTful JSON API.
  • Ad-hoc and schema-free with a flat address space.
  • Distributed, featuring robust, incremental replication with bi-directional conflict detection and management.
  • Recently merged with Membase
  • The CouchDB file layout and commitment system features all
  • Atomic Consistent Isolated Durable (ACID) properties.
  • Document updates (add, edit, delete) are serialized, except for binary blobs which are written concurrently.
  • CouchDB read operations use a Multi-Version Concurrency Control (MVCC) model where each client sees a consistent snapshot of the database from the beginning to the end of the read operation.
  • Eventually Consistent
  • Common Advantages of CouchDB
    • Cheap, easy to implement (open source)
    • Data are replicated to multiple nodes (therefore identical and fault-tolerant) and can be partitioned
    • Down nodes easily replaced
    • No single point of failure
    • Easy to distribute
    • Don't require a schema
    • Can scale up and down
    • Relax the data consistency requirement (CAP)

    CouchDB vs MongoDB :

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    CouchDB vs Couchbase :

    Earlier there was an affinity towards the similar names. Behind each of these names there is a story. Damien Katz initiated the Couchbase, who was actually the founder of CouchDB, a combination of CouchDB and Membase is called Couchbase, leading to make an easily scalable and high performance database.
  • 1. Open Source Type
    • An apache open source project written in the Erlang language is CouchDB and is freely downloadable by the user. Another open source language is couch base, but it has community, enterprise and developer editions as a group of components.
  • 2. Database Lock
    • For ensuring the table or a row, DBMS will use lock and that is what traditional DBMS is all about. In the CouchDB there is no lock as it uses a concept called MVCC (Multi Version Concurrency Control). Pessimistic locking is used by Couchbase on the other hand.
  • 3.Query language
    • Couchbase has its own query language called N1QL, a SQL-like query language for JSON. CouchDB doesn’t have Query language. They both have similar views that is multi-dimensional/geospatial.
  • 4. Topology
    • Couchbase topology is distributed and it means it is built from forms and scratch a cluster of nodes. The owner for a portion of hash space has each node in the cluster.
    • On the other hand Couch DB is imitated and is master-master replication, making multi-site application easy for deployment.
    • In the form of key-document MongoDB is widely used in application development. It has pros and cons over CouchDB and Couch database.

    couchbase vs mongodb :

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    Couchbase vs Cassandra :

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