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6.
Atomicity
All operations will occur, or none
will occur
Simple example:
INSERT INTO Names
(firstname,lastname) VALUES (Sean,
Collins)
7.
Consistency
All operations will leave the
database in a known good state
Keys, Constraints, triggers, etc..
Cannot have operations that violate
the rules for your data
Customer doesn’t exist
Primary key that already exists
8.
Isolation
Operations cannot interfere with one-
another
Handle multiple, concurrent
operations (One write, many reads) in
a defined manner.
9.
Durability
Completed operations are bullet-proof
Yank out the power cable
Crash the database server process
When the database server comes back
up - database is in a consistent
state - with your data intact.
10.
CAP
CAP Theorem - Eric Brewer
(Conjecture)
Seth Gilbert and Nancy Lynch
(Theorem)
Consistency
Availability
Partition Tolerance
11.
Consistency
All nodes in a distributed system see
the same data - at that exact moment
Simple example: Update item B on
node #1, query node #2 about B -
get back the updated data
12.
Availability
System will process requests, despite
failures in individual nodes
Not a guarantee that the operation
will succeed
Just a guarantee that you will get a
response back
No guarantee is made for WHEN you
will get a response back
13.
Partition Tolerance
System will continue to operate, even
when arbitrarily many messages
between nodes are lost
14.
PICK TWO
CAP Theorem asserts that of the three
properties, a system can only have
two.
15.
Data Types
Relational Database
Tables
Columns
Rows
16.
Common NoSQL
Datatypes
Key/Value
Column Store
Document
etc....
17.
ACID vs. BASE
Someone clever... har har
“Basic Availability”
“Soft State”
“Eventually Consistent”
Much prefer CAP theorem - exposes the
tradeoffs that you have to choose
between
Editor's Notes
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