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NoSQL Distilled
Its not a free lunch
#NoSQLDistilled
@pramodsadalage
[email protected]
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Why RDBMS?
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ACID Transactions
Atomicity
Consistency
Isolation
Durability
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Standard Query
Interface(SQL)
SELECT
name,age,startdate
FROM
student
SELECT
startdate, count(*)
FROM
student
GROUP BY startdate
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Interact with many
languages
def exec_sql_return_rows(sql)
rows = Array.new
$db_connection.exec sql do | row |
rows << row[0]
end
rows
end
try {
statement = connection.createStatement();
resultSet = statement.executeQuery(sql);
process(resultSet);
} catch(SQLException e) {
//deal with exception
}
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Everyone knows SQL
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Limit less indexing
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Handles many data models
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Why NoSQL
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Schema changes are hard
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Impedance mismatch
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Application vs Integration
databases
Integration Database
Common for all used cases
E-Commerce
Recommendation
Application Database
Specialized storage for each
used cases
E-Commerce
Recommendation
Service
Integration
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Running on clusters
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Un-Structured Data
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Un-Even rate of data growth
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Domain Models
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Domain driven data models
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RDBMS data
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Aggregate model
(Embedding objects)
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// in customers
{
"id": 1,
"name": "Martin",
"billingAddress": [{"city": "Chicago"}],
"orders": [
{
"id":99,
"orderItems":[
{
"productId":27,
"price": 32.45,
"productName": "NoSQL Distilled"
}
],
"shippingAddress":[{"city":"Chicago"}]
"orderPayment":[
{
"ccinfo":"1000-1000-1000-1000",
"txnId":"abelif879rft",
"billingAddress": {"city": "Chicago"}
}
],
}
]
}
Representing Aggregate
Data
Key
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Aggregate model
(Referencing Objects)
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// in Customers
{
"id":1,
"name":"Martin",
"billingAddress":[{"city":"Chicago"}]
}
// in Orders
{
"id":99,
"customerId":1,
"orderItems":[
{
"productId":27,
"price": 32.45,
"productName": "NoSQL Distilled"
}
],
"shippingAddress":[{"city":"Chicago"}]
"orderPayment":[
{
"ccinfo":"1000-1000-1000-1000",
"txnId":"abelif879rft",
"billingAddress": {"city": "Chicago"}
}
],
}
Representing Aggregate
data
Key
Key Reference
Key
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Aggregate Orientation
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RDBMS’s have no concept of
aggregates
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Aggregates reduce the need
for ACID
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Better for clusters, can be
distributed easily
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Key-Value
Document
Column-Family
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Key Value Databases
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Key-Value
Database
•One Key-One Value
•Value is opaque to database
•Like a Hash
•Some are distributed
Oracle Riak
instance cluster
table bucket
row key-value
row-id key
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“key” (VIN) “value” (car facts)
JTTDR…
…
make#Ford
model#Mustang
year#2011
….
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Session Storage
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User Profiles/Preferences
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Shopping Cart
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Single user analytics
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Document Databases
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Document
Database
•One Key-One Value
•Value is visible to database
•Value can be queries
•JSON/XML documents
Oracle MongoDB
instance mongod
schema database
table collection
row document
row_id _id
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“id” (VIN) “document” (car facts)
JTTDR…
{…
“make”: “Ford”,
“model”: “Mustang”,
“year”: 2011,
…
}
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Event Logging
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Prototype development
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eCommerce Application
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Content Management
Applications
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Column-Family Databases
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Column-Family
Database
•Data organized as columns
•Each row has row key
•Columns have versioned data
•Row data is sorted by
column name
Oracle Cassandra
instance cluster
database keyspace
table column-family
row row
columns
same for
every row
columns can
be different
for each row
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“id” (VIN) “column families”(car facts)
JTTDR…
{…
“car”:{“make”: “Ford”,
“model”: “focus”…}
“service”:{…}
}
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Large write volume
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Content Management
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eCommerce Application
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Graph Databases
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No content
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Graph
Databases
•Is multi-relational graph
•Relationships are first-
class citizens
•Traversal algorithms
•Nodes and Edges can have
data (key-value pairs)
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Graph databases work best
for data with complex
relations
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Connected Data
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Routing things/money
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Location Services
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Recommendation engines
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Schema-less really?
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Schema-free does not mean
no schema/data-migration
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Schema is implicit in code
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Data must be migrated,
when schema in code
changes
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All data need not be
migrated at the same time
(lazy migration)
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Polyglot Persistence
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Use different data storage
technology for varying
needs
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Can be across the
enterprise or in single
application
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Encapsulate data access
through services
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Order persistence service
Document store
e-commerce platform
Session/Cart storage
service
Key-Value store
Inventory and Price
service
RDBMS
(Legacy DB)
Nodes and Relations
service
Graph store
Shopping cart and
session data
Completed
Orders
Inventory
and
Item Price Customer social
graph
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RDBMS
e-commerce
platform
Shopping cart
data
Completed
Orders
Session data
SOLR
Search
requests
Update Indexed
Data
Update indexed data,
batch or realtime
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Did I not say something
about free lunch?
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Given all the choice, the
decision to choose the right
database is yours.
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Choose for programmer
productivity
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Choose for data access
performance
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Choose to stick with the
default
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Choose by testing your
expectations
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Try the databases, they are
all open-source
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Thanks
#NoSQLDistilled
@pramodsadalage
sadalage.com