JSONB

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GA releases for CockroachDB v23.1 are no longer supported. Cockroach Labs will stop providing LTS Assistance Support for v23.1 LTS releases on November 13, 2025. Prior to that date, upgrade to a more recent version to continue receiving support. For more details, refer to the Release Support Policy.

The JSONB data type stores JSON (JavaScript Object Notation) data as a binary representation of the JSONB value, which eliminates whitespace, duplicate keys, and key ordering. JSONB supports GIN indexes.

Tip:

For a hands-on demonstration of storing and querying JSON data from a third-party API, see the JSON tutorial.

Alias

In CockroachDB, JSON is an alias for JSONB.

Note:

In PostgreSQL, JSONB and JSON are two different data types. In CockroachDB, the JSONB / JSON data type is similar in behavior to the JSONB data type in PostgreSQL.

Syntax

The syntax for the JSONB data type follows the format specified in RFC8259. You can express a constant value of type JSONB using an interpreted literal or a string literal annotated with type JSONB.

There are six types of JSONB values:

null
Boolean
String
Number (i.e., decimal, not the standard int64)
Array (i.e., an ordered sequence of JSONB values)
Object (i.e., a mapping from strings to JSONB values)

Examples:

'[{"foo":"bar"}]'
'{"type": "account creation", "username": "harvestboy93"}'
'{"first_name": "Ernie", "status": "Looking for treats", "location" : "Brooklyn"}'
'{"prices" : [ { "05/01/2022" : 100.5 } , { "06/01/2022" : 101.5 } ]}'

Note:

If duplicate keys are included in the input, only the last value is kept.

Size

The size of a JSONB value is variable, but we recommend that you keep values under 1 MB to ensure satisfactory performance. Above that threshold, write amplification and other considerations may cause significant performance degradation.

Warning:

We strongly recommend adding size limits to all indexed columns, which includes columns in primary keys.

Values exceeding 1 MiB can lead to storage layer write amplification and cause significant performance degradation or even crashes due to OOMs (out of memory errors).

To add a size limit using CREATE TABLE:

CREATE TABLE name (first STRING(100), last STRING(100));

To add a size limit using ALTER TABLE ... ALTER COLUMN:

SET enable_experimental_alter_column_type_general = true;

ALTER TABLE name ALTER first TYPE STRING(99);

Operators

Operator	Description	Example Query and Output
`->`	Access a `JSONB` field, returning a `JSONB` value.	`SELECT '[{"foo":"bar"}]'::JSONB->0->'foo';` `"bar"::JSONB`
`->>`	Access a `JSONB` field, returning a string.	`SELECT '{"foo":"bar"}'::JSONB->>'foo';` `bar::STRING`
`@>`	Tests whether the left `JSONB` field contains the right `JSONB` field.	`SELECT ('{"foo": {"baz": 3}, "bar": 2}'::JSONB@>'{"foo": {"baz":3}}'::JSONB );` `true`
`>@`	Tests whether the left `JSONB` field is contained by the right `JSONB` field.	`SELECT('{"bar":2}'::JSONB<@'{"foo":1, "bar":2}'::JSONB);` `true`
`#>`	Access a `JSONB` field at the specified path, returning a `JSONB` value.	`SELECT '[{"foo":"bar"}]'::JSONB#>'{0,foo}';` `"bar"::JSONB`
`#>>`	Access a `JSONB` field at the specified path, returning a string.	`SELECT '[{"foo":"bar"}]'::JSONB#>>'{0,foo}';` `bar::STRING`
`?`	Does the key or element string exist within the JSONB value?	`SELECT('{"foo":1, "bar":2}'::JSONB?'bar');` `true`
`?&`	Do all the key or element strings exist within the JSONB value?	`SELECT('{"foo":1, "bar":2}'::JSONB?&array['foo','bar']);` `true`
`?\|`	Do any of the key or element strings exist within the JSONB value?	`SELECT('{"foo":1, "bar":2}'::JSONB?\|array['bar']);` `true`
`[` ... `]`	Access a `JSONB` key, returning a `JSONB` value or object. For details, see Subscripted expressions.	`SELECT('{"foo": {"bar":1}}'::JSONB)['foo']['bar'];` `1`

For the full list of supported JSONB operators, see Operators.

Functions

Function	Description
`jsonb_array_elements(<jsonb>)`	Expands a `JSONB` array to a set of `JSONB` values. See Map a `JSONB` array field into rows.
`jsonb_build_object(<any_element>...)`	Builds a `JSONB` object out of a variadic argument list that alternates between keys and values.
`jsonb_each(<jsonb>)`	Expands the outermost `JSONB` object into a set of key-value pairs. See Retrieve key-value pairs from a `JSONB` field.
`jsonb_object_keys(<jsonb>)`	Returns sorted set of keys in the outermost `JSONB` object. See Retrieve the distinct keys from a `JSONB` field.
`jsonb_pretty(<jsonb>)`	Returns the given `JSONB` value as a `STRING` indented and with newlines. See Retrieve formatted `JSONB` data.
`jsonb_set(val: jsonb, path: string[], to: jsonb)`	Returns the JSON value pointed to by the variadic arguments. See Update an array element.

For the full list of supported JSONB functions, see JSONB functions.

Index `JSONB` data

To index a JSONB column you can use a GIN index or index an expression on the column.

Known limitations

You cannot use primary key, foreign key, and unique constraints on JSONB values.
You cannot use comparison operators (such as < or >) on JSONB elements. For example, the following query does not work and returns an error:

  SELECT '{"a": 1}'::JSONB -> 'a' < '{"b": 2}'::JSONB -> 'b';

  ERROR: unsupported comparison operator: <jsonb> < <jsonb>
  SQLSTATE: 22023

Tracking GitHub issue

You cannot order queries using JSONB and JSON-typed columns.

Tracking issue
If the execution of a join query exceeds the limit set for memory-buffering operations (i.e., the value set for the sql.distsql.temp_storage.workmem cluster setting), CockroachDB will spill the intermediate results of computation to disk. If the join operation spills to disk, and at least one of the columns is of type JSON, CockroachDB returns the error unable to encode table key: *tree.DJSON. If the memory limit is not reached, then the query will be processed without error.

Tracking issue

Examples

This section shows how to create tables with JSONB columns and use operators and functions to access and update JSONB data. For the full list of operators and functions, see Operators and JSONB functions.

Create a table with a `JSONB` column

CREATE TABLE users (
    profile_id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    last_updated TIMESTAMP DEFAULT now(),
    user_profile JSONB
  );

SHOW COLUMNS FROM users;

  column_name  | data_type | is_nullable |  column_default   | generation_expression |  indices     | is_hidden
---------------+-----------+-------------+-------------------+-----------------------+--------------+------------
  profile_id   | UUID      |    false    | gen_random_uuid() |                       | {users_pkey} |   false
  last_updated | TIMESTAMP |    true     | now():::TIMESTAMP |                       | {users_pkey} |   false
  user_profile | JSONB     |    true     | NULL              |                       | {users_pkey} |   false
(3 rows)

INSERT INTO users (user_profile) VALUES
    ('{"first_name": "Lola", "last_name": "Dog", "location": "NYC", "online" : true, "friends" : 547}'),
    ('{"first_name": "Ernie", "status": "Looking for treats", "location" : "Brooklyn"}');

SELECT * FROM users;

+--------------------------------------+----------------------------------+----------------------------------------------------------------------------------------------+
|              profile_id              |           last_updated           |                               user_profile                                                   |
+--------------------------------------+----------------------------------+----------------------------------------------------------------------------------------------+
| 33c0a5d8-b93a-4161-a294-6121ee1ade93 | 2022-02-27 16:39:28.155024+00:00 | {"first_name": "Lola", "friends": 547, "last_name": "Dog", "location":"NYC", "online": true} |
| 6a7c15c9-462e-4551-9e93-f389cf63918a | 2022-02-27 16:39:28.155024+00:00 | {"first_name": "Ernie", "location": "Brooklyn", "status": "Looking for treats}               |
+--------------------------------------+----------------------------------+----------------------------------------------------------------------------------------------+

Retrieve formatted `JSONB` data

To retrieve JSONB data with easier-to-read formatting, use the jsonb_pretty() function. For example, retrieve data from the table you created in the first example:

SELECT profile_id, last_updated, jsonb_pretty(user_profile) FROM users;

+--------------------------------------+----------------------------------+------------------------------------+
|              profile_id              |           last_updated           |            jsonb_pretty            |
+--------------------------------------+----------------------------------+------------------------------------+
| 33c0a5d8-b93a-4161-a294-6121ee1ade93 | 2022-02-27 16:39:28.155024+00:00 | {                                  |
|                                      |                                  |     "first_name": "Lola",          |
|                                      |                                  |     "friends": 547,                |
|                                      |                                  |     "last_name": "Dog",            |
|                                      |                                  |     "location": "NYC",             |
|                                      |                                  |     "online": true                 |
|                                      |                                  | }                                  |
| 6a7c15c9-462e-4551-9e93-f389cf63918a | 2022-02-27 16:39:28.155024+00:00 | {                                  |
|                                      |                                  |     "first_name": "Ernie",         |
|                                      |                                  |     "location": "Brooklyn",        |
|                                      |                                  |     "status": "Looking for treats" |
|                                      |                                  | }                                  |
+--------------------------------------+----------------------------------+------------------------------------+

Retrieve a specific field from `JSONB` data

To retrieve a specific field from JSONB data, use the -> operator. For example, to retrieve a field from the table you created in Create a table with a JSONB column, run:

SELECT user_profile->'first_name',user_profile->'location' FROM users;

  ?column? |  ?column?
-----------+-------------
  "Ernie"  | "Brooklyn"
  "Lola"   | "NYC"

You can also use a subscripted expression for an equivalent result:

SELECT (user_profile)['first_name'],(user_profile)['location'] FROM users;

  user_profile | user_profile
---------------+---------------
  "Ernie"      | "Brooklyn"
  "Lola"       | "NYC"

Use the ->> operator to return JSONB fields as STRING values:

SELECT user_profile->>'first_name', user_profile->>'location' FROM users;

  ?column? | ?column?
-----------+-----------
  Ernie    | Brooklyn
  Lola     | NYC

Use the @> operator to filter the values in a field in a JSONB column:

SELECT user_profile->'first_name', user_profile->'location' FROM users WHERE user_profile @> '{"location":"NYC"}';

  ?column? | ?column?
-----------+-----------
  "Lola"   | "NYC"

Use the #>> operator with a path to return all first names:

SELECT user_profile#>>'{first_name}' as "first name" from users;

  first name
--------------
  Ernie
  Lola
(2 rows)

Retrieve the distinct keys from a `JSONB` field

SELECT DISTINCT jsonb_object_keys(user_profile) AS keys FROM users;

     keys
--------------
  first_name
  friends
  last_name
  location
  online
  status
(6 rows)

Retrieve key-value pairs from a `JSONB` field

SELECT jsonb_each(user_profile) AS pairs FROM users;

                pairs
-------------------------------------
  (first_name,"""Lola""")
  (friends,547)
  (last_name,"""Dog""")
  (location,"""NYC""")
  (online,true)
  (first_name,"""Ernie""")
  (location,"""Brooklyn""")
  (status,"""Looking for treats""")
(8 rows)

Group and order `JSONB` values

To organize your JSONB field values, use the GROUP BY and ORDER BY clauses with the ->> operator. For example, organize the first_name values from the table you created in the first example:

For this example, we will add a few more records to the existing table. This will help us see clearly how the data is grouped.

INSERT INTO users (user_profile) VALUES
    ('{"first_name": "Lola", "last_name": "Kim", "location": "Seoul", "online": false, "friends": 600}'),
    ('{"first_name": "Parvati", "last_name": "Patil", "location": "London", "online": false, "friends": 500}');

SELECT user_profile->>'first_name' AS first_name, user_profile->>'location' AS location FROM users;

  first_name | location
-------------+-----------
  Ernie      | Brooklyn
  Lola       | NYC
  Parvati    | London
  Lola       | Seoul

Group and order the data.

SELECT user_profile->>'first_name' first_name, count(*) total FROM users group by user_profile->>'first_name' order by total;

  first_name | total
-------------+-------
  Ernie      | 1
  Parvati    | 1
  Lola       | 2

The ->> operator returns STRING and uses string comparison rules to order the data. If you want numeric ordering, cast the resulting data to FLOAT.

Map a `JSONB` array field into rows

To map a JSONB array field into rows, use the jsonb_array_elements function:

CREATE TABLE commodity (id varchar(10), data jsonb);
INSERT INTO commodity (id, data) values ('silver', '{"prices" : [ { "05/01/2022" : 100.5 } , { "06/01/2022" : 101.5 } ]}');
INSERT INTO commodity (id, data) values ('gold', '{"prices" : [ { "05/01/2022" : 200.5 } , { "06/01/2022" : 211.5 } ]}');
SELECT * FROM commodity;

    id   |                            data
---------+-------------------------------------------------------------
  silver | {"prices": [{"05/01/2022": 100.5}, {"06/01/2022": 101.5}]}
  gold   | {"prices": [{"05/01/2022": 200.5}, {"06/01/2022": 211.5}]}
(2 rows)

SELECT id as commodity, jsonb_array_elements(commodity.data->'prices') AS "price" FROM commodity;

  commodity |         price
------------+------------------------
  silver    | {"05/01/2022": 100.5}
  silver    | {"06/01/2022": 101.5}
  gold      | {"05/01/2022": 200.5}
  gold      | {"06/01/2022": 211.5}
(4 rows)

Access nested `JSONB` fields

To display the commodity prices for May, run:

SELECT id AS commodity, data->'prices'->0->'05/01/2022' AS "May prices" from commodity;

  commodity | May prices
------------+-------------
  silver    |      100.5
  gold      |      200.5
(2 rows)

Update an array element

To update a field value, use the jsonb_set function. For example, to update the price of silver on 06/01/2022 to 90.5, run:

UPDATE commodity SET data = jsonb_set(data, '{prices, 1, "06/01/2022"}', '90.5') where id = 'silver';
UPDATE 1

SELECT * FROM commodity;

    id   |                            data
---------+-------------------------------------------------------------
  silver | {"prices": [{"05/01/2022": 100.5}, {"06/01/2022": 90.5}]}
  gold   | {"prices": [{"05/01/2022": 200.5}, {"06/01/2022": 211.5}]}
(2 rows)

Create a table with a `JSONB` column and a computed column

In this example, create a table with a JSONB column and a stored computed column:

> CREATE TABLE student_profiles (
    id STRING PRIMARY KEY AS (profile->>'id') STORED,
    profile JSONB
);

Create a compute column after you create a table:

> ALTER TABLE student_profiles ADD COLUMN age INT AS ( (profile->>'age')::INT) STORED;

Then, insert a few rows of data:

> INSERT INTO student_profiles (profile) VALUES
    ('{"id": "d78236", "name": "Arthur Read", "age": "16", "school": "PVPHS", "credits": 120, "sports": "none"}'),
    ('{"name": "Buster Bunny", "age": "15", "id": "f98112", "school": "THS", "credits": 67, "clubs": "MUN"}'),
    ('{"name": "Ernie Narayan", "school" : "Brooklyn Tech", "id": "t63512", "sports": "Track and Field", "clubs": "Chess"}');

> SELECT * FROM student_profiles;

+--------+---------------------------------------------------------------------------------------------------------------------+------+
|   id   |                                                       profile                                                       | age  |
---------+---------------------------------------------------------------------------------------------------------------------+------+
| d78236 | {"age": "16", "credits": 120, "id": "d78236", "name": "Arthur Read", "school": "PVPHS", "sports": "none"}           |   16 |
| f98112 | {"age": "15", "clubs": "MUN", "credits": 67, "id": "f98112", "name": "Buster Bunny", "school": "THS"}               |   15 |
| t63512 | {"clubs": "Chess", "id": "t63512", "name": "Ernie Narayan", "school": "Brooklyn Tech", "sports": "Track and Field"} | NULL |
+--------+---------------------------------------------------------------------------------------------------------------------+------|

The primary key id is computed as a field from the profile column. Additionally the age column is computed from the profile column data as well.

This example shows how add a stored computed column with a coerced type:

CREATE TABLE json_data (
    id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    json_info JSONB
);
INSERT INTO json_data (json_info) VALUES ('{"amount": "123.45"}');

ALTER TABLE json_data ADD COLUMN amount DECIMAL AS ((json_info->>'amount')::DECIMAL) STORED;

SELECT * FROM json_data;

                   id                  |      json_info       | amount
---------------------------------------+----------------------+---------
  e7c3d706-1367-4d77-bfb4-386dfdeb10f9 | {"amount": "123.45"} | 123.45
(1 row)

Create a table with a `JSONB` column and a virtual computed column

In this example, create a table with a JSONB column and virtual computed columns:

> CREATE TABLE student_profiles (
    id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    profile JSONB,
    full_name STRING AS (concat_ws(' ',profile->>'firstName', profile->>'lastName')) VIRTUAL,
    birthday TIMESTAMP AS (parse_timestamp(profile->>'birthdate')) VIRTUAL
);

Then, insert a few rows of data:

> INSERT INTO student_profiles (profile) VALUES
    ('{"id": "d78236", "firstName": "Arthur", "lastName": "Read", "birthdate": "2010-01-25", "school": "PVPHS", "credits": 120, "sports": "none"}'),
    ('{"firstName": "Buster", "lastName": "Bunny", "birthdate": "2011-11-07", "id": "f98112", "school": "THS", "credits": 67, "clubs": "MUN"}'),
    ('{"firstName": "Ernie", "lastName": "Narayan", "school" : "Brooklyn Tech", "id": "t63512", "sports": "Track and Field", "clubs": "Chess"}');

> SELECT * FROM student_profiles;

                   id                  |                                                                   profile                                                                   |   full_name   |      birthday
---------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------+---------------+----------------------
  0e420282-105d-473b-83e2-3b082e7033e4 | {"birthdate": "2011-11-07", "clubs": "MUN", "credits": 67, "firstName": "Buster", "id": "f98112", "lastName": "Bunny", "school": "THS"}     | Buster Bunny  | 2011-11-07 00:00:00
  6e9b77cd-ec67-41ae-b346-7b3d89902c72 | {"birthdate": "2010-01-25", "credits": 120, "firstName": "Arthur", "id": "d78236", "lastName": "Read", "school": "PVPHS", "sports": "none"} | Arthur Read   | 2010-01-25 00:00:00
  f74b21e3-dc1e-49b7-a648-3c9b9024a70f | {"clubs": "Chess", "firstName": "Ernie", "id": "t63512", "lastName": "Narayan", "school": "Brooklyn Tech", "sports": "Track and Field"}     | Ernie Narayan | NULL
(3 rows)


Time: 2ms total (execution 2ms / network 0ms)

The virtual column full_name is computed as a field from the profile column's data. The first name and last name are concatenated and separated by a single whitespace character using the concat_ws string function.

The virtual column birthday is parsed as a TIMESTAMP value from the profile column's birthdate string value. The parse_timestamp function is used to parse strings in TIMESTAMP format.

Supported casting and conversion

This section describes how to cast and convert JSONB values.

You can cast all JSONB values to the following data type:

STRING

You can cast numeric JSONB values to the following numeric data types:

For example:

SELECT '100'::JSONB::INT;

  int8
--------
   100
(1 row)

SELECT '100000'::JSONB::FLOAT;

  float8
----------
  100000
(1 row)

SELECT '100.50'::JSONB::DECIMAL;

  numeric
-----------
   100.50
(1 row)

You can use the parse_timestamp function to parse strings in TIMESTAMP format.

SELECT parse_timestamp ('2022-05-28T10:53:25.160Z');

      parse_timestamp
--------------------------
2022-05-28 10:53:25.16
(1 row)

You can use the parse_timestamp function to retrieve string representations of timestamp data within JSONB columns in TIMESTAMP format.

CREATE TABLE events (
  raw JSONB,
  event_created TIMESTAMP AS (parse_timestamp(raw->'event'->>'created')) VIRTUAL
);
INSERT INTO events (raw) VALUES ('{"event":{"created":"2022-05-28T10:53:25.160Z"}}');
SELECT event_created FROM events;

CREATE TABLE

INSERT 1

      event_created
--------------------------
  2022-05-28 10:53:25.16
(1 row)

Cockroach
University

Docs Hub

JSONB

Alias

Syntax

Size

Operators

Functions

Index `JSONB` data

Known limitations

Examples

Create a table with a `JSONB` column

Retrieve formatted `JSONB` data

Retrieve a specific field from `JSONB` data

Retrieve the distinct keys from a `JSONB` field

Retrieve key-value pairs from a `JSONB` field

Group and order `JSONB` values

Map a `JSONB` array field into rows

Access nested `JSONB` fields

Update an array element

Create a table with a `JSONB` column and a computed column

Create a table with a `JSONB` column and a virtual computed column

Supported casting and conversion

See also

Cockroach University

Docs Hub

Cockroach University

Docs Hub

JSONB

Alias

Syntax

Size

Operators

Functions

Index JSONB data

Known limitations

Examples

Create a table with a JSONB column

Retrieve formatted JSONB data

Retrieve a specific field from JSONB data

Retrieve the distinct keys from a JSONB field

Retrieve key-value pairs from a JSONB field

Group and order JSONB values

Map a JSONB array field into rows

Access nested JSONB fields

Update an array element

Create a table with a JSONB column and a computed column

Create a table with a JSONB column and a virtual computed column

Supported casting and conversion

See also

Cockroach
University

Cockroach
University

Index `JSONB` data

Create a table with a `JSONB` column

Retrieve formatted `JSONB` data

Retrieve a specific field from `JSONB` data

Retrieve the distinct keys from a `JSONB` field

Retrieve key-value pairs from a `JSONB` field

Group and order `JSONB` values

Map a `JSONB` array field into rows

Access nested `JSONB` fields

Create a table with a `JSONB` column and a computed column

Create a table with a `JSONB` column and a virtual computed column