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Are Relational Databases the Only Type of Databases? A Brief DB History Early 1970s Many database systems Incompatible, exposing many implementation details Then Ted Codd came along Relational model Structured Query Language (SQL) Implementation differences became irrelevant A few major DB systems dominated the market Then Web 2.0 & 3.0, Big Data Happen What do you think happen? Semi-structured data happen. •A lot of it and in many forms… Some Facts about Web x.0 and Big Data Twitter: 255 million monthly active users and 500 million Tweets are sent per day, Facebook: over 1 billion monthly users and faces 3 million message per 20 minute Instagram: 200 Million Monthly Active Users and 1.6 Billion Likes and 60 Million Photos shared every day Database Systems Landscape Nowadays Somebody, Please, Bring Some Order to This Madness – Cont’d Somebody, Please, Bring Some Order to This Madness – Cont’d NoSQL Databases Somebody, Please, Bring Some Order to This Madness Different Interfaces Different hardware support Different application support Lack of Uniformity Source: http://www.infoq.com/articles/State-of-NoSQL Database Evolution Timeline Additional Resources Tutorial by C. Mohan, An In-Depth Look at Modern Database Systems https://docs.google.com/file/d/0B7lNUaak 0bK1encwYnBVUWZSWjA/edit Key-Value Store Implemented as an associative array, map, symbol table, or dictionary abstract data type composed of a collection of (key, value) pairs such that each possible key appears at most once in the collection. A simple put/get interface Great properties: scalability, availability, reliability Key-Value Store Usage Scenarios Increasingly popular within data centers and in P2P Data center amazon.com LinkedIn Facebook Dynamo Voldemort Cassandra P2P Vuze uTorrent Vuze DHT uTorrent DHT Row Store and Column Store Source: Column-Oriented Database Systems, VLDB 2009. Tutorial; S. Harizopoulos, D. Abadi, P. Boncz In row store data are stored in the disk tuple by tuple. Where in column store data are stored in the disk column by column. Column-stores are more I/O efficient for read-only queries as they read, only those attributes which are accessed by a query. Row Store and Column Store Row Store Column Store (+) Easy to add/modify a record (+) Only need to read in relevant data (-) Might read in unnecessary data (-) Tuple writes require multiple accesses So column stores are suitable for read-mostly, read-intensive, large data repositories Graph Databases Biological Network Ecological Network Social Network Chemical Network Program Flow Web Graph Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke 16 Graph Databases: Query Find all the restaurants my friends (in Facebook) like So, What Does CS Curricula Cover? Undergrad Database Courses Introduction to Relational Databases Grad Database Courses Advanced Relational Databases in IS&T Principles of Data Management in CS • Still relational DBMS. How about the rest of database system types? Good question… Where is most of the research activity going on nowadays? Good question again… So, Why Do We Emphasize Relational DBs? Jack Clark, The Register, 30 August 2013: “The tech world is turning back toward SQL, bringing to a close a possibly misspent half-decade in which startups courted developers with promises of infinite scalability and the finest imitation-Google tools available, and companies found themselves exposed to unstable data and poor guarantees.” Google Spanner paper, October 2012: “We believe it is better to have application programmers deal with performance problems due to overuse of transactions as bottlenecks arise, rather than always coding around the lack of transactions.” Sean Doherty in Wired, September 2013: “But don’t become unnecessarily distracted by the shiny, new-fangled, NoSQL red buttons just yet. Relational databases may not be hot or sexy but for your important data there is no substitute.” And, The Key Reason of All Gartner estimates RDBMS market at $26B with about 9% annual growth, whereas Market Research Media Ltd expects NoSQL market to be at $3.5B by 2018. Source: C Mohan’s tutorial Databases make these folks happy ... End users and DBMS vendors DB application programmers E.g., smart webmasters Database administrator (DBA) Designs logical /physical schemas Handles security and authorization Data availability, crash recovery Database tuning as needs evolve Must understand how a DBMS works! Summary DBMS used to maintain, query large datasets. Benefits include recovery from system crashes, concurrent access, quick application development, data integrity and security. Levels of abstraction give data independence. A DBMS typically has a layered architecture. DBAs hold responsible jobs and are well-paid! DBMS R&D is one of the broadest, most exciting areas in CS. I Want to Hear from You!