In a database management system following the relational 
model, a view is a virtual table representing the result of 
a database query. Whenever an ordinary view's table is 
queried or updated, the DBMS converts these into queries or 
updates against the underlying base tables. A materialized 
view takes a different approach in which the query result 
is cached as a concrete table that may be updated from the 
original base tables from time to time. This enables much 
more efficient access, at the cost of some data being 
potentially out-of-date. It is most useful in data 
warehousing scenarios, where frequent queries of the actual 
base tables can be extremely expensive.

In addition, because the view is manifested as a real 
table, anything that can be done to a real table can be 
done to it, most importantly building indexes on any 
column, enabling drastic speedups in query time. In a 
normal view, it's typically only possible to exploit 
indexes on columns that come directly from (or have a 
mapping to) indexed columns in the base tables; often this 
functionality is not offered at all.

Materialized views were implemented first by the Oracle 
database.

There are three types of materialized views:

1) Read only

Cannot be updated and complex materialized views are 
supported 
2) Updateable

Can be updated even when disconnected from the master site. 
Are refreshed on demand. 
Consumes fewer resources. 
Requires Advanced Replication option to be installed. 
3) Writeable

Created with the for update clause. 
Changes are lost when view is refreshed. 
Requires Advanced Replication option to be installed

**A materialized view provides indirect access to table data
by storing the results of a query in a separate schema
object. Unlike an ordinary view, which does not take up any
storage space or contain any data.
**You can define a materialized view on a base table,
partitioned table or view and you can define indexes on a
materialized view.
**Materialized views are schema objects that can be used to
summarize, precompute, replicate, and distribute data. E.g.
to construct a data warehouse