+ NoSQL W2013 CSCI 2141

NoSQL W2013 CSCI 2141

OLTP vs. OLAP We can divide IT systems into transactional (OLTP) and analytical (OLAP). In general we can assume that OLTP systems provide source data to data warehouses, whereas OLAP systems help to analyze it .

Challenges of Scale Differ

A Comparison of SQL and NoSQL Databases Slides from: Keith W. Hare Metadata Open Forum More reading: http://martinfowler.com/articles/nosqlKeyPoints.html Metadata Open Forum

Abstract NoSQL databases (either no-SQL or Not Only SQL) are currently a hot topic in some parts of computing. In fact, one website lists over a hundred different NoSQL databases. This presentation reviews the features common to the NoSQL databases and compares those features to the features and capabilities of SQL databases. BIG DATA! 6 May 9, 2023

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8 SQL Characteristics Data stored in columns and tables Relationships represented by data Data Manipulation Language Data Definition Language Transactions Abstraction from physical layer May 9, 2023

9 SQL Physical Layer Abstraction Applications specify what, not how Query optimization engine Physical layer can change without modifying applications Create indexes to support queries In Memory databases May 9, 2023

Data Manipulation Language (DML) Data manipulated with Select, Insert, Update, & Delete statements 10 Select T1.Column1, T2.Column2 From Table1, Table2 Where T1.Column1 T2.Column1 Data Aggregation Compound statements Functions and Procedures Explicit transaction control May 9, 2023

Data Definition Language Schema defined at the start Create Table (Column1 Datatype1, Column2 Datatype 2, ) Constraints to define and enforce relationships 11 Primary Key Foreign Key Etc. Triggers to respond to Insert, Update , & Delete Stored Modules Alter Drop Security and Access Control May 9, 2023

Transactions – ACID Properties Atomic – All of the work in a transaction completes (commit) or none of it completes Consistent – A transaction transforms the database from one consistent state to another consistent state. Consistency is defined in terms of constraints. Isolated – The results of any changes made during a transaction are not visible until the transaction has committed. Durable – The results of a committed transaction survive failures 12 May 9, 2023

NewSQL: more OLTP throughput, real-time analytics ) SQL as the primary mechanism for application interaction 2) ACID support for transactions 3) A non-locking concurrency control mechanism so realtime reads will not conflict with writes, and thereby cause them to stall. 4) An architecture providing much higher per-node performance than available from the traditional "elephants” 5) A scale-out, shared-nothing architecture, capable of running on a large number of nodes without bottlenecking

NoSQL Definition From www.nosql-database.org: Next Generation Databases mostly addressing some of the points: being nonrelational, distributed, open-source and horizontal scalable. The original intention has been modern web-scale databases. 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. 14 May 9, 2023

NoSQL Products/Projects http://www.nosql-database.org/ lists 122 NoSQL Databases Cassandra CouchDB Hadoop & Hbase MongoDB StupidDB Etc. 15 May 9, 2023

NoSQL Products/Projects http://www.nosql-database.org/ lists 122 NoSQL Databases Cassandra CouchDB Hadoop & Hbase MongoDB StupidDB Etc. 16 May 9, 2023

NoSQL Distinguishing Characteristics Asynchronous 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 Inserts & Updates Schema-less ACID transaction properties are not needed – BASE CAP Theorem Open source development May 9, 2023 17

BASE Transactions Acronym contrived to be the opposite of ACID Basically Available, Soft state, Eventually Consistent Characteristics Weak consistency – stale data Availability first Best effort Approximate answers OK Aggressive (optimistic) Simpler and faster 18 OK May 9, 2023

Brewer’s CAP Theorem A distributed system can support only two of the following characteristics: 19 Consistency Availability Partition tolerance May 9, 2023

NoSQL Database Types Discussing NoSQL databases is complicated because there are a variety of types: Column Store – Each storage block contains data from only one column Document Store – stores documents made up of tagged elements Key-Value 21 Store – Hash table of keys May 9, 2023

Other Non-SQL Databases XML Databases Graph Databases Codasyl Object Databases Oriented Databases Etc Will 22 not address these today May 9, 2023

Storing and Modifying Data Syntax varies HTML Java Script Etc. Asynchronous – Inserts and updates do not wait for confirmation Versioned Optimistic 25 Concurrency May 9, 2023

Retrieving Data Syntax Varies No set-based query language Procedural program languages such as Java, C, etc. Application No query optimizer Quick May 26 specifies retrieval path answer is important not be a single “right” answer May 9, 2023

27 Open Source Small upfront software costs Suitable for large scale distribution on commodity hardware May 9, 2023

NoSQL Summary NoSQL databases reject: Overhead of ACID transactions “Complexity” of SQL Burden of up-front schema design Declarative query expression Yesterday’s technology Programmer responsible for Step-by-step procedural language Navigating access path 28 May 9, 2023

Summary SQL Databases Predefined Schema Standard definition and interface language Tight consistency Well defined semantics NoSQL Database No predefined Schema Per-product definition and interface language Getting an answer quickly is more important than getting a correct answer 29 May 9, 2023

30 Web References “NoSQL -- Your Ultimate Guide to the Non - Relational Universe!” http://nosql-database.org/links.html “NoSQL (RDBMS)” http://en.wikipedia.org/wiki/NoSQL PODC Keynote, July 19, 2000. Towards Robust. Distributed Systems. Dr. Eric A. Brewer. Professor, UC Berkeley. CoFounder & Chief Scientist, Inktomi . www.eecs.berkeley.edu/ brewer/cs262b-2004/PODCkeynote.pdf “Brewer's CAP Theorem” posted by Julian Browne, January 11, 2009. http://www.julianbrowne.com/article/viewer/brewerscap-theorem “How to write a CV” Geek & Poke Cartoon http://geekandpoke.typepad.com/geekandpoke/2011/01/nosql.h tml May 9, 2023

31 Web References “Exploring CouchDB: A document-oriented database for Web applications”, Joe Lennon, Software developer, Core International. http://www.ibm.com/developerworks/opensource/l ibrary/os-couchdb/index.html “Graph Databases, NOSQL and Neo4j” Posted by Peter Neubauer on May 12, 2010 at: http://www.infoq.com/articles/graph-nosql-neo4j “Cassandra vs MongoDB vs CouchDB vs Redis vs Riak vs HBase comparison”, Kristóf Kovács. http://kkovacs.eu/cassandra-vs-mongodb-vscouchdb-vs-redis “Distinguishing Two Major Types of ColumnStores” Posted by Daniel Abadi onMarch 29, 2010 http://dbmsmusings.blogspot.com/2010/03/disting uishing-two-major-types-of 29.html May 9, 2023

Web References “MapReduce: Simplified Data Processing on Large Clusters”, Jeffrey Dean and Sanjay Ghemawat, December 2004. http://labs.google.com/papers/mapreduce.html “Scalable SQL”, ACM Queue, Michael Rys, April 19, 2011 http://queue.acm.org/detail.cfm?id 1971597 “a practical guide to noSQL”, Posted by Denise Miura on March 17, 2011 at http://blogs.marklogic.com/2011/03/17/apractical-guide-to-nosql/ 32 May 9, 2023