gayathrinosql.pptx

gayathrinosql.pptx

• 2.
  NoSQL databases arecurrently a hot topic in some parts of computing, with over a hundred different NoSQL databases. NoSQL stands for: No Relational No RDBMS Not Only SQL NoSQL is an umbrella term for all databases and data stores that don’t follow the RDBMS principles A class of products A collection of several (related) concepts about data storage and manipulation Often related to large data sets
• 3.
  Non-relational DBMSs arenot new But NoSQL represents a new incarnation Due to massively scalable Internet applications Based on distributed and parallel computing Development Starts with Google First research paper published in 2003 Continues also thanks to Lucene's developers/Apache (Hadoop) and Amazon (Dynamo) Then a lot of products and interests came from Facebook, Netfix, Yahoo, eBay, Hulu, IBM, and many more
• 4.
  Three major paperswere the seeds of the NoSQL movement BigTable (Google) Dynamo (Amazon) Distributed key-value data store Eventual consistency CAP Theorem (discuss in a sec ..)
• 5.
  NoSQL comes fromInternet, thus it is often related to the “big data” concept How much big are “big data”? Over few terabytes Enough to start spanning multiple storage units Challenges Efficiently storing and accessing large amounts of data is difficult, even more considering fault tolerance and backups Manipulating large data sets involves running immensely parallel processes Managing continuously evolving schema and metadata for semi-structured and un-structured data is difficult
• 6.
  Discussing NoSQL databasesis complicated because there are a variety of types: Sorted ordered Column Store Optimized for queries over large datasets, and store columns of data together, instead of rows Document databases: pair each key with a complex data structure known as a document. Key-Value Store : are the simplest NoSQL databases. Every single item in the database is stored as an attribute name (or 'key'), together with its value. Graph Databases : are used to store information about networks of data, such as social connections.
• 7.
  Documents Loosely structured setsof key/value pairs in documents, e.g., XML, JSON, BSON Encapsulate and encode data in some standard formats or encodings Are addressed in the database via a unique key Documents are treated as a whole, avoiding splitting a document into its constituent name/value pairs Allow documents retrieving by keys or contents Notable for: MongoDB (used in FourSquare, Github, and more) CouchDB (used in Apple, BBC, Canonical, Cern, and more)
• 8.
  Store data ina schema-less way Store data as maps HashMaps or associative arrays Provide a very efficient average running time algorithm for accessing data Notable for: Couchbase (Zynga, Vimeo, NAVTEQ, ...) Redis (Craiglist, Instagram, StackOverfow, flickr, ...) Amazon Dynamo (Amazon, Elsevier, IMDb, ...) Apache Cassandra (Facebook, Digg, Reddit, Twitter,...) Voldemort (LinkedIn, eBay, …) Riak (Github, Comcast, Mochi, ...)
• 9.
  Data are storedin a column-oriented way Data efficiently stored Avoids consuming space for storing nulls Columns are grouped in column-families Data isn’t stored as a single table but is stored by column families Unit of data is a set of key/value pairs Identified by “row-key” Ordered and sorted based on row-key Notable for: Google's Bigtable (used in all Google's services) HBase (Facebook, StumbleUpon, Hulu, Yahoo!, ...)
• 10.
  • Consistency andAvailability is not “binary” decision • AP systems relax consistency in favor of availability – but are not inconsistent • CP systems sacrifice availability for consistency- but are not unavailable • This suggests both AP and CP systems can offer a degree of consistency, and availability, as well as partition tolerance
• 11.
  THANK YOU