Optimizes read requests and eliminates the need for multiple write requests by duplicating data from a base table.

Optimizes read requests by allowing different partitioning and clustering columns than the base table and eliminates the need for individual write requests to multiple tables. When data is written to the base table, it is also automatically written to all associated materialized views.
  • Use all base table primary keys in the materialized view.
  • Multiple non-primary key columns from the base table are supported when the partition key is the same as in the base table, otherwise only a single non-primary key from the base table is allowed in the materialized view's PRIMARY KEY.
  • Static columns are not supported.
  • Exclude rows with null values in the materialized view primary key column.
  • A materialized view cannot be created in a different keyspace from the base table. You also cannot create a materialized view in the system tables.


CREATE MATERIALIZED VIEW [ IF NOT EXISTS ] [keyspace_name.]view_name
  AS SELECT [ (column_list) ]
  FROM [keyspace_name.]table_name
  WHERE column_name IS NOT NULL [ AND column_name IS NOT NULL ... ]
    [ AND relation [ AND ... ] ] 
  PRIMARY KEY (column_list)
  [ WITH [ table_properties ]
    [ [ AND ] CLUSTERING ORDER BY (cluster_column_name order_option) ] ] ;
Table 1. Legend
Syntax conventions Description
UPPERCASE Literal keyword.
Lowercase Not literal.
Italics Variable value. Replace with a user-defined value.
[] Optional. Square brackets ( [] ) surround optional command arguments. Do not type the square brackets.
( ) Group. Parentheses ( ( ) ) identify a group to choose from. Do not type the parentheses.
| Or. A vertical bar ( | ) separates alternative elements. Type any one of the elements. Do not type the vertical bar.
... Repeatable. An ellipsis ( ... ) indicates that you can repeat the syntax element as often as required.
'Literal string' Single quotation ( ' ) marks must surround literal strings in CQL statements. Use single quotation marks to preserve upper case.
{ key : value } Map collection. Braces ( { } ) enclose map collections or key value pairs. A colon separates the key and the value.
<datatype1,datatype2> Set, list, map, or tuple. Angle brackets ( < > ) enclose data types in a set, list, map, or tuple. Separate the data types with a comma.
cql_statement; End CQL statement. A semicolon ( ; ) terminates all CQL statements.
[--] Separate the command line options from the command arguments with two hyphens ( -- ). This syntax is useful when arguments might be mistaken for command line options.
' <schema> ... </schema> ' Search CQL only: Single quotation marks ( ' ) surround an entire XML schema declaration.
@xml_entity='xml_entity_type' Search CQL only: Identify the entity and literal value to overwrite the XML element in the schema and solrConfig files.

Optional. Suppresses the error message when attempting to create a materialized view that already exists. Use to continue executing commands, such as a SOURCE command. The option only validates that a materialized view with the same name exists; columns, primary keys, properties and other settings can differ.

Optional. When no keyspace is selected or to create the view in another keyspace, set the keyspace name before the materialized view name.
Note: Base tables and materialized views are always in the same keyspace.

Materialized view names can only contain alpha-numeric characters and underscores. The view name must begin with a number or letter and can be up to 49 characters long.


Comma-separated list of non-PRIMARY KEY columns from the base table to include in the materialized view. All primary key columns are automatically included.

Static columns, even when specified, are not included in the materialized view.

PK_column_name IS NOT NULL

Test all primary key columns for null values in the where clause. Separate each condition with AND. Rows with null values in the primary key are not inserted into the materialized view table.

AND relation

Other relations that target the specific data needed.

PRIMARY KEY (column_list)

Comma-separated list of columns used to partition and cluster the data. You can add a single non-primary key column from the base table. Reorder the primary keys as needed to query the table more efficiently, including changing the partitioning and clustering keys.

List the partition key first, followed by the clustering keys. Create a compound partition key by enclosing column names in parenthesis, for example:
  ( PK_column1[, PK_column2 ...] ) ,
    clustering_column1[, clustering_column2 ... ] )
Optional. Specify table properties if different than default. Separate table property definitions with an AND. See table properties.
Note: The base table properties are not copied.
Restriction: Change log, CDC, is not available for materialized views. Not all table properties are available when creating a materialized view; for example, default_time_to_live is not available.


This section shows example scenarios that illustrate the use of materialized views.

Basic example of a materialized view

This cyclist_base table is used in the first example scenario:
CREATE TABLE IF NOT EXISTS cycling.cyclist_base (
  name text, 
  age int, 
  birthday date, 
  country text
The following materialized view cyclist_by_age uses the base table cyclist_base. The WHERE clause ensures that only rows whose age and cid columns are non-NULL are added to the materialized view. In the materialized view, age is the partition key, and cid is the clustering column. In the base table, cid is the partition key.
CREATE MATERIALIZED VIEW cycling.cyclist_by_age AS
  SELECT age, cid, birthday, country, name
  FROM cycling.cyclist_base 
  PRIMARY KEY (age, cid)
    AND caching = { 'keys' : 'ALL', 'rows_per_partition' : '100' }
    AND comment = 'Based on table cyclist';
The results of this query:
FROM cycling.cyclist_by_age;
 age | cid                                  | birthday   | country       | name
  28 | 6ab09bec-e68e-48d9-a5f8-97e6fb4c9b47 | 1987-06-07 |   Netherlands |   Steven KRUIKSWIJK
  19 | 1c526849-d3a2-42a3-bcf9-7903c80b3d16 | 1998-12-23 |     Australia |       Kanden GROVES
  19 | 410919ef-bd1b-4efa-8256-b0fd8ab67029 | 1999-01-04 |    Uzbekistan | Iskandarbek SHODIEV
  18 | 15a116fc-b833-4da6-ab9a-4a7775752836 | 1997-08-19 | United States |        Adrien COSTA
  18 | 18f471bf-f631-4bc4-a9a2-d6f6cf5ea503 | 1997-03-29 |   Netherlands |         Bram WELTEN
  18 | ffdfa2a7-5fc6-49a7-bfdc-3fcdcfdd7156 | 1997-02-08 |   Netherlands |    Pascal EENKHOORN
  22 | e7ae5cf3-d358-4d99-b900-85902fda9bb0 | 1993-06-18 |   New Zealand |          Alex FRAME
  27 | c9c9c484-5e4a-4542-8203-8d047a01b8a8 | 1987-09-04 |        Brazil |     Cristian EGIDIO
  27 | d1aad83b-be60-47a4-bd6e-069b8da0d97b | 1987-09-04 |       Germany |     Johannes HEIDER
  20 | 862cc51f-00a1-4d5a-976b-a359cab7300e | 1994-09-04 |       Denmark |       Joakim BUKDAL
  38 | 220844bf-4860-49d6-9a4b-6b5d3a79cbfb | 1977-07-08 |         Italy |     Paolo TIRALONGO
  29 | 96c4c40d-58c8-4710-b73f-681e9b1f70ae | 1989-04-20 |     Australia |     Benjamin DYBALL

(12 rows)

Using a materialized view to perform queries that are not possible on a base table

The following scenario shows how to use a materialized view to perform queries that are not possible on a base table unless ALLOW FILTERING is used. ALLOW FILTERING is not recommended because of the performance degradation. This table stores the cycling team mechanic information:
CREATE TABLE IF NOT EXISTS cycling.mechanic (
  emp_id int,
  dept_id int,
  name text,
  age int,
  birthdate date,
  PRIMARY KEY (emp_id, dept_id)
The table contains these rows:
 emp_id | dept_id | age | birthdate  | name
      5 |       3 |  25 | 1996-10-04 | Lisa SMITH
      1 |       1 |  21 | 1992-06-18 | Fred GREEN
      2 |       1 |  22 | 1993-01-15 | John SMITH
      4 |       2 |  24 | 1995-08-19 | Jack JONES
      3 |       2 |  23 | 1994-02-07 |   Jane DOE

(5 rows)
This materialized view selects the columns from the previous table and contains a different primary key from the table:
  SELECT emp_id, dept_id, name, age, birthdate
  FROM cycling.mechanic
    AND dept_id IS NOT NULL
    AND name IS NOT NULL
    AND birthdate IS NOT NULL
  PRIMARY KEY (age, emp_id, dept_id);
This query retrieves the rows where the age is 21:
FROM cycling.mechanic_view
WHERE age = 21;
The previous query cannot be run on the base table without ALLOW FILTERING. The output from the previous query is as follows:
 age | emp_id | dept_id | birthdate  | name
  21 |      1 |       1 | 1992-06-18 | Fred GREEN

(1 rows)