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Iran Hutchinson.  I work for InterSystems who drives the new NoSQL project. 

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Presentation on theme: "Iran Hutchinson.  I work for InterSystems who drives the new NoSQL project. "— Presentation transcript:

1 Iran Hutchinson

2  I work for InterSystems who drives the new http://globalsdb.org NoSQL project. http://globalsdb.org  Email: iran.hutchinson@intersystems.comiran.hutchinson@intersystems.com  Twitter: #iranic  Skype: chatwithiran

3  … NoSQL Databases  Understanding what they are  Understanding how to leverage their strengths  Understanding their weaknesses  Staying away from hype and religious wars  Fighting your developer demon

4  Edgar Frank “Ted” Codd  Known for 12 Rules (0 ~ 12) for Relational Data Systems

5  Rule 1: The information Rule  All information is represented in 1 and only 1 way, namely by values in column positions within rows of tables  Rule 12: The no subversion Rule  If the system provides a low-level (record-at-a- time) interface, then that interface cannot be used to subvert the system i.e. relational security or integrity constraints.

6  Simple APIs  Java Example: Document.save(myObject)  Seamless language integration  No impedance mismatch  Designed to be horizontally scalable (elastic)  Flexible data model  Majority free and/or Open Source  Free and Commercial production support

7  Proven  Available talent / Well-known  AD-Hoc querying  Scalable (limits?)  Free and Commercial production support

8  Interface for data access  Limited horizontal scalability?  Impedance mismatches  Programming model  In-flexible data model

9  Does not include the underlying data structure.  B-tree and B+-trees can be fast and efficient  The relational model + SQL can limit B-trees

10  Class of data management systems inherently  Non-relational  Distributed  Horizontally scalable  With optional schemas  Providing simple APIs  Term Not-Only-SQL recently embraced  Dave Kellog’s Blog Post Dave Kellog’s Blog Post

11  No to ACID  No to the impedance mismatch with SQL  Dealing with Big Data and Web Scale  High prices from RDBMS vendors  Use commodity hardware  Flexible data models  It’s a cool movement ….

12 NNo RRemember MUMPS? SSET ^Car("Door","Color")="BLUE” RRemember Multi-value/PICK MMATWRITE array.variable ON file.variable,id. …. EEver heard of the NoSQL RDB?

13 Data Key-ValueDocumentColumnGraph

14  This depends on your use case.  Example  http://www.mongodb.org/display/DOCS/Use+Cas es  Compare your problems to others.  Example:  http://wiki.apache.org/hadoop/PoweredBy

15  http://nosql-database.org/ lists 122 today. http://nosql-database.org/  Depends on your model selection.  Most likely choose well-known project.  Don’t forget about shared risk!

16  Some solutions have no querying  When available query languages differ  Lack of general AD-Hoc querying – “no” SQL  NOTE: Toad for CloudToad for Cloud

17  Skills  Data Model  Data format  Tools  Standards?

18  Some databases are not as proven  Incomplete NoSQL solutions  You write a larger data management tier  You maintain your business code and infrastructure code  You have to customize management and deployment technology and procedures

19  Know your application  Don’t forget the past lessons  Consider a hybrid approach  Fight the desire to Roll-Your-Own-DB  Start small but significant

20  Two Systems  NoSQL + SQL/RDBMS  Updates  Real-time  Asynchronous or Batch NoSQL SQL/RDB MS Data Mapper / Translato r

21  One system does both NoSQL and SQL Data RelationalKey-ValueDocumentColumnGraph?

22  InterSystems Caché supports SQL and NoSQL  Production NoSQL for 20+ years  APIs for.NET, Java, Perl, Python, etc.  Expanding paradigms for more use cases.  Comes the closest to approach 2 Data RelationalKey-ValueDocumentColumnGraph?

23  Core of InterSystems Caché  Free for development and production  Simple APIs Java and JavaScript  http://globalsdb.org http://globalsdb.org  Sponsored by InterSystems Data ArrayDocument?

24  Over time I think we will see  NoSQL features in mainstream databases  NoSQL offerings by more commercial companies  Dominant open source / free NoSQL projects  New definitions of enterprise databases

25  Hadoop/Hbase  Cassandra  MongoDB  CouchDB  Riak  Couchbase  Neo4J

26  InterSystems Caché  SimpleDB  Azure Table Storage  Google App Engine Data Storage  Mark Logic Server  Infinite Graph  Riak (has open source version)  Berkely DB


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