Aggregate Data Models
Unit 2
Parul Pandey
• A data model is the model through which we
perceive and manipulate our data.
• The dominant data model of the last couple of
decades is the relational data model, which is best
visualized as a set of tables.
• One of the most obvious shifts with NoSQL is a
move away from the relational model
• Different data models - key-value, document,
column-family, and graph
• First three share a common characteristic of their
data models which we will call aggregate
orientation.
Aggregates
• The relational model - information - tuples (rows).
• Tuple is a limited data structure: It captures a set of
values, so you cannot nest one tuple within another to get
nested records, nor can you put a list of values or tuples
within another. It allows us to think of all operations as
operating on and returning tuples.
• Aggregate orientation takes a different approach. D
– data in units that have a more complex structure than a set of
tuples. It can be handy to think in terms of a complex record
that allows lists and other record structures to be nested inside
it.
• Aggregate is a collection of related objects that we
wish to treat as a unit. In particular, it is a unit for data
manipulation and management of consistency
• Dealing in aggregates makes it much easier for these
databases to handle operating on a cluster, since
theaggregate makes a natural unit for replication and
sharding.
• Aggregates are also often easier for application
programmers to work with, since they often
manipulate data through aggregate structures.
Example of Relations and Aggregates
• Let’s assume we have to build an e-commerce
website; we are going to be selling items
directly to customers over the web, and we
will have to store information about users, our
product catalog, orders, shipping addresses,
billingaddresses, and payment data.
Consequences of Aggregate Orientation
• The relational mapping captures the various data elements
- without any notion of an aggregate entity.
• For eg. an order consists of order items, a shipping address,
and a payment.
• This can be expressed in the relational model in terms of
foreign key relationships—but there is nothing to
distinguish relationships that represent aggregations from
those that don’t.
• As a result, the database can’t use a knowledge of
aggregate structure to help it store and distribute the data.
• Aggregate-oriented databases - semantics to consider by
focusing on the unit of interaction with the data storage
It’s all about how the data is being used by applications.
• Relational databases, graph databases - aggregate-ignorant
• aggregate structure may help with some data interactions but be an
obstacle for others.
• difficult to draw aggregate boundaries well, particularly if the same
data is used in many different contexts.
• order makes a good aggregate when a customer is making and
reviewing orders, and when the retailer is processing orders.
• However, if a retailer wants to analyze its product sales over the last
few months, then an order aggregate becomes a trouble. To get to
product sales history, you’ll have to dig into every aggregate in the
database.
• The clinching reason for aggregate orientation is
that it helps greatly with running on a cluster,
• we need to minimize how many nodes we need to
query when we are gathering data.
• Aggregates, give the database important
information about which bits of data will be
manipulated together, and thus should live on the
same node.
• NoSQL databases don’t support ACID transactions
and thus sacrifice consistency
