Scalable SQL

Group 11

Sameera Shah & Fatemah Husain

[10/31/13]

Relevance to the course

1) Relational Databases2) Transaction Processing

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Motivation

Why SQL?

1) Scale to a large number of users2) Accommodate large data3) Allows addition/removal resources quickly

Approaches to Scaling SQL1) Use of function+ data partitioning

2) Each partition will use relational DBa) Provides local consistencyb) Query processing

3) Mirroring of nodes a) Guarantee node availability

4) Eventual consistency as acceptable global consistencyAdvantages:

a) Provides availability during node failuresb) Ability to work on older data

Disadvantage:c) Trade-off with consistency

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Scalable Architectures For Scale-OutFunction + Data partitioning

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Scalable Architecture Application Requirements

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Consistency

Availability

Partition tolerance

CAP Theorem: You can have at most two of these properties for any shared-data system.

ACID (SQL) VS. BASE (NoSQL)

1) Basically Available

2) Soft state

3) Eventual Consistency

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1) Atomicity

2) Consistency

3) Isolation

4) Durability

VS.

Summary

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SQL NoSQL

Definition A database structured to recognize relations among stored items of information

“Not Only SQL”, is an approach to data management and database design that's useful for very large sets of distributed data.

Characteristics

Pre-defined Schema Schema-less

ACID properties BASE Properties

Structured Data Unstructured and Semi Structured data

Database Examples

Commercial: Oracle, MS SQLOpen Source: MySQL, Ingres

Column: HBaseDocument: MongoDB Key-value: DynamoGraph: Virtuoso

References

1) Scalable SQL: How do large-scale sites and applications remain SQL-based? Michael Rys, Communications of the ACM Vol. 54 No. 6, Pages 48-53 10.1145/1953122.1953141

2) Relational DB: http://en.wikipedia.org/wiki/Relational_databaseText Book: Elmasri, Navathe, Fundamentals of Database Systems, 6th, Addison Wesley, ISBN-10: 0-13-608620-9.

3) CAP: http://en.wikipedia.org/wiki/CAP_theorem

4) NoSQL: http://en.wikipedia.org/wiki/NoSQL

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THANK YOU