Some CockroachDB features are made available in phases prior to being launched in general availability (GA). This page defines the different levels of CockroachDB v23.2 feature availability and lists the features in each phase.
This page outlines feature availability, which is separate from Cockroach Labs' Release Support Policy or API Support Policy.
Feature availability phases
Phase | Definition | Accessibility |
---|---|---|
Private preview | Feature is available to select customers and not publicly documented. | Invite-only |
Limited access | Feature is publicly documented but not yet available widely. This feature may have limitations and/or capabilities that may change or be added based on feedback, before being promoted to GA. | Opt-in Contact your Cockroach Labs account team. |
Preview | Feature is publicly available and documented. This feature may have limitations and/or capabilities that may change or be added based on feedback, before being promoted to GA. | Public |
General availability (GA) | Feature is publicly available and documented. | Public |
Any feature made available in a phase prior to GA is provided without any warranties of any kind. Such features are not subject to any technical support or uptime availability commitments unless Cockroach Labs explicitly states otherwise in writing.
Features in limited access
The following features are in limited access and are subject to change. To begin validating a limited access feature and share feedback and/or issues, contact Support.
Export logs to Azure Monitor
Exporting logs to Azure Monitor from your CockroachDB Dedicated cluster hosted on Azure is in limited access. Once the export is configured, logs will flow from all nodes in all regions of your CockroachDB Dedicated cluster to Azure Monitor. To express interest and try it out, contact Support.
Export metrics to Azure Monitor
Exporting Metrics to Azure Monitor from a CockroachDB Dedicated cluster hosted on Azure is in limited access. Once the export is configured, metrics will flow from all nodes in all regions of your CockroachDB Dedicated cluster to your chosen cloud metrics sink. To express interest and try it out, contact Support.
AWS PrivateLink for CockroachDB Serverless
Connecting privately to a multi-region CockroachDB Serverless cluster using AWS PrivateLink is in limited access. This can help your organization meet its security requirements and reduce your cluster's exposure to public networks. To express interest and try it out, contact Support.
Features in preview
The following features are in preview and are subject to change. To share feedback and/or issues, contact Support.
CockroachDB Cloud Folders
Organizing CockroachDB Cloud clusters using folders is in preview. Folders allow you to organize and manage access to your clusters according to your organization's requirements. For example, you can create top-level folders for each business unit in your organization, and within those folders, organize clusters by geographic location and then by level of maturity, such as production, staging, and testing.
Custom Metrics Chart page for CockroachDB Cloud clusters
The Custom Metrics Chart page for CockroachDB Cloud clusters allows you to create custom charts showing the time series data for an available metric or combination of metrics.
Export metrics from CockroachDB Dedicated clusters
Exporting metrics from CockroachDB Dedicated to AWS CloudWatch or Datadog using the Cloud API is in preview. Once the export is configured, metrics will flow from all nodes in all regions of your CockroachDB Dedicated cluster to your chosen cloud metrics sink.
Exporting metrics to Azure Monitor is in limited access. Refer to Exporting metrics to Azure Monitor.
Convert a schema from Oracle or Microsoft SQL Server
Using the Migrations page to convert a schema from Oracle or Microsoft SQL Server is in preview.
Schema conversion summary report
The schema-conversion summary report in the Migrations page is in preview. This report displays the results of the schema analysis and provides bulk actions you can apply to update the schema, is in preview.
SQL Shell
The SQL Shell in the CockroachDB Cloud Console is in preview. The SQL Shell enables you to run queries on your CockroachDB Cloud cluster directly from your browser.
Restore a CockroachDB Dedicated cluster from a managed-service backup
Restoring an entire CockroachDB Dedicated cluster from a managed-service backup is in preview. Managed-service backups are automated backups of clusters in CockroachDB Cloud that are stored in Cockroach Labs' cloud storage.
Log SQL Statistics to Datadog
You can log sampled_query
and sampled_transaction
events to Datadog for finer granularity and long-term retention of SQL statistics, and to reduce the performance impacts of logging these events locally. The sampled_query
events and the sampled_transaction
events contain common SQL event and execution details for transactions, and statements.
CockroachDB supports a built-in integration with Datadog which sends these events as logs via the Datadog HTTP API. This integration is the recommended path to achieve high throughput data ingestion, which will in turn provide more query and transaction events for greater workload observability.
Custom Metrics Chart page for CockroachDB Cloud clusters
The Custom Metrics Chart page for CockroachDB Cloud clusters allows you to create custom charts showing the time series data for an available metric or combination of metrics.
Log SQL Statistics to Datadog
Configure logging of sampled_query
events to Datadog for finer granularity and long-term retention of SQL statistics. The sampled_query
events contain common SQL event and execution details for sessions, transactions, and statements.
CockroachDB supports a built-in integration with Datadog which sends query events as logs via the Datadog HTTP API. This integration is the recommended path to achieve high throughput data ingestion, which will in turn provide more query events for greater workload observability.
Role-based SQL audit logging
Role-based SQL audit logging gives you detailed information about queries being executed against your system by specific users or roles. An event of type role_based_audit_event
is recorded when an executed query belongs to a user whose role membership corresponds to a role that is enabled to emit an audit log via the sql.log.user_audit
cluster setting. The event is logged in the SENSITIVE_ACCESS
logging channel.
Table-based SQL audit logging
With table-based SQL audit logging you can log all queries against a table to a file, for security purposes. For more information, see ALTER TABLE ... EXPERIMENTAL_AUDIT
.
> ALTER TABLE t EXPERIMENTAL_AUDIT SET READ WRITE;
Show table fingerprints
Table fingerprints are used to compute an identification string of an entire table, for the purpose of gauging whether two tables have the same data. This is useful, for example, when restoring a table from backup.
Example:
> SHOW EXPERIMENTAL_FINGERPRINTS FROM TABLE t;
index_name | fingerprint
------------+---------------------
primary | 1999042440040364641
(1 row)
KV event tracing
Use session tracing (via SHOW TRACE FOR SESSION
) to report the replicas of all KV events that occur during its execution.
Example:
> SET tracing = on;
> SELECT * from t;
> SET tracing = off;
> SHOW EXPERIMENTAL_REPLICA TRACE FOR SESSION;
timestamp | node_id | store_id | replica_id
----------------------------------+---------+----------+------------
2018-10-18 15:50:13.345879+00:00 | 3 | 3 | 7
2018-10-18 15:50:20.628383+00:00 | 2 | 2 | 26
Check for constraint violations with SCRUB
Checks the consistency of UNIQUE
indexes, CHECK
constraints, and more. Partially implemented; see cockroachdb/cockroach#10425 for details.
This example uses the users
table from our open-source, fictional peer-to-peer vehicle-sharing application, MovR.
> EXPERIMENTAL SCRUB table movr.users;
job_uuid | error_type | database | table | primary_key | timestamp | repaired | details
----------+--------------------------+----------+-------+----------------------------------------------------------+---------------------------+----------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
| index_key_decoding_error | movr | users | ('boston','0009eeb5-d779-4bf8-b1bd-8566533b105c') | 2018-10-18 16:00:38.65916 | f | {"error_message": "key ordering did not match datum ordering. IndexDescriptor=ASC", "index_name": "primary", "row_data": {"address": "e'06484 Christine Villages\\nGrantport, TN 01572'", "city": "'boston'", "credit_card": "'4634253150884'", "id": "'0009eeb5-d779-4bf8-b1bd-8566533b105c'", "name": "'Jessica Webb'"}}
| index_key_decoding_error | movr | users | ('los angeles','0001252c-fc16-4006-b6dc-c6b1a0fd1f5b') | 2018-10-18 16:00:38.65916 | f | {"error_message": "key ordering did not match datum ordering. IndexDescriptor=ASC", "index_name": "primary", "row_data": {"address": "e'91309 Warner Springs\\nLake Danielmouth, PR 33400'", "city": "'los angeles'", "credit_card": "'3584736360686445'", "id": "'0001252c-fc16-4006-b6dc-c6b1a0fd1f5b'", "name": "'Rebecca Gibson'"}}
| index_key_decoding_error | movr | users | ('new york','000169a5-e337-4441-b664-dae63e682980') | 2018-10-18 16:00:38.65916 | f | {"error_message": "key ordering did not match datum ordering. IndexDescriptor=ASC", "index_name": "primary", "row_data": {"address": "e'0787 Christopher Highway Apt. 363\\nHamptonmouth, TX 91864-2620'", "city": "'new york'", "credit_card": "'4578562547256688'", "id": "'000169a5-e337-4441-b664-dae63e682980'", "name": "'Christopher Johnson'"}}
| index_key_decoding_error | movr | users | ('paris','00089fc4-e5b1-48f6-9f0b-409905f228c4') | 2018-10-18 16:00:38.65916 | f | {"error_message": "key ordering did not match datum ordering. IndexDescriptor=ASC", "index_name": "primary", "row_data": {"address": "e'46735 Martin Summit\\nMichaelview, OH 10906-5889'", "city": "'paris'", "credit_card": "'5102207609888778'", "id": "'00089fc4-e5b1-48f6-9f0b-409905f228c4'", "name": "'Nicole Fuller'"}}
| index_key_decoding_error | movr | users | ('rome','000209fc-69a1-4dd5-8053-3b5e5769876d') | 2018-10-18 16:00:38.65916 | f | {"error_message": "key ordering did not match datum ordering. IndexDescriptor=ASC", "index_name": "primary", "row_data": {"address": "e'473 Barrera Vista Apt. 890\\nYeseniaburgh, CO 78087'", "city": "'rome'", "credit_card": "'3534605564661093'", "id": "'000209fc-69a1-4dd5-8053-3b5e5769876d'", "name": "'Sheryl Shea'"}}
| index_key_decoding_error | movr | users | ('san francisco','00058767-1e83-4e18-999f-13b5a74d7225') | 2018-10-18 16:00:38.65916 | f | {"error_message": "key ordering did not match datum ordering. IndexDescriptor=ASC", "index_name": "primary", "row_data": {"address": "e'5664 Acevedo Drive Suite 829\\nHernandezview, MI 13516'", "city": "'san francisco'", "credit_card": "'376185496850202'", "id": "'00058767-1e83-4e18-999f-13b5a74d7225'", "name": "'Kevin Turner'"}}
| index_key_decoding_error | movr | users | ('seattle','0002e904-1256-4528-8b5f-abad16e695ff') | 2018-10-18 16:00:38.65916 | f | {"error_message": "key ordering did not match datum ordering. IndexDescriptor=ASC", "index_name": "primary", "row_data": {"address": "e'81499 Samuel Crescent Suite 631\\nLake Christopherborough, PR 50401'", "city": "'seattle'", "credit_card": "'38743493725890'", "id": "'0002e904-1256-4528-8b5f-abad16e695ff'", "name": "'Mark Williams'"}}
| index_key_decoding_error | movr | users | ('washington dc','00007caf-2014-4696-85b0-840e7d8b6db9') | 2018-10-18 16:00:38.65916 | f | {"error_message": "key ordering did not match datum ordering. IndexDescriptor=ASC", "index_name": "primary", "row_data": {"address": "e'4578 Holder Trafficway\\nReynoldsside, IL 23520-7418'", "city": "'washington dc'", "credit_card": "'30454993082943'", "id": "'00007caf-2014-4696-85b0-840e7d8b6db9'", "name": "'Marie Miller'"}}
(8 rows)
Super regions
Super regions allow you to define a set of database regions such that schema objects will have all of their replicas stored only in regions that are members of the super region. The primary use case for super regions is data domiciling.
Export metrics from CockroachDB Dedicated clusters
CockroachDB Dedicated users can use the Cloud API to configure metrics export to AWS CloudWatch or Datadog. Once the export is configured, metrics will flow from all nodes in all regions of your CockroachDB Dedicated cluster to your chosen cloud metrics sink.
Show range information for a specific row
The SHOW RANGE ... FOR ROW
statement shows information about a range for a particular row of data. This information is useful for verifying how SQL data maps to underlying ranges, and where the replicas for a range are located.
Alter column types
CockroachDB supports altering the column types of existing tables, with certain limitations. To enable altering column types, set the enable_experimental_alter_column_type_general
session variable to true
.
Temporary objects
Temporary tables, temporary views, and temporary sequences are in preview in CockroachDB. If you create too many temporary objects in a session, the performance of DDL operations will degrade. Performance limitations could persist long after creating the temporary objects. For more details, see cockroachdb/cockroach#46260.
To enable temporary objects, set the experimental_enable_temp_tables
session variable to on
.
Password authentication without TLS
For deployments where transport security is already handled at the infrastructure level (e.g., IPSec with DMZ), and TLS-based transport security is not possible or not desirable, CockroachDB supports delegating transport security to the infrastructure with the flag --accept-sql-without-tls
for cockroach start
.
With this flag, SQL clients can establish a session over TCP without a TLS handshake. They still need to present valid authentication credentials, for example a password in the default configuration. Different authentication schemes can be further configured as per server.host_based_authentication.configuration
.
Example:
$ cockroach sql --user=jpointsman --insecure
# Welcome to the CockroachDB SQL shell.
# All statements must be terminated by a semicolon.
# To exit, type: \q.
#
Enter password:
Core implementation of changefeeds
The EXPERIMENTAL CHANGEFEED FOR
statement creates a new core changefeed, which streams row-level changes to the client indefinitely until the underlying connection is closed or the changefeed is canceled. A core changefeed can watch one table or multiple tables in a comma-separated list.
Changefeed metrics labels
To measure metrics per changefeed, you can define a "metrics label" for one or multiple changefeed(s). The changefeed(s) will increment each changefeed metric. Metrics label information is sent with time-series metrics to http://{host}:{http-port}/_status/vars
, viewable via the Prometheus endpoint. An aggregated metric of all changefeeds is also measured.
It is necessary to consider the following when applying metrics labels to changefeeds:
- Metrics labels are not available in CockroachDB Serverless.
- Metrics labels are not supported as tags in Datadog.
- The
server.child_metrics.enabled
cluster setting must be set totrue
before using themetrics_label
option. - Metrics label information is sent to the
_status/vars
endpoint, but will not show up indebug.zip
or the DB Console. - Introducing labels to isolate a changefeed's metrics can increase cardinality significantly. There is a limit of 1024 unique labels in place to prevent cardinality explosion. That is, when labels are applied to high-cardinality data (data with a higher number of unique values), each changefeed with a label then results in more metrics data to multiply together, which will grow over time. This will have an impact on performance as the metric-series data per changefeed quickly populates against its label.
- The maximum length of a metrics label is 128 bytes.
For usage details, see the Monitor and Debug Changefeeds page.
Google Pub/Sub sink for changefeeds
Changefeeds can deliver messages to a Google Cloud Pub/Sub sink, which is integrated with Google Cloud Platform.
Multiple active portals
The multiple active portals feature of the Postgres wire protocol (pgwire) is available, with limitations. For more information, see Multiple active portals.
Physical Cluster Replication
New in v23.2: Physical cluster replication continuously sends all data at the byte level from a primary cluster to an independent standby cluster. Existing data and ongoing changes on the active primary cluster, which is serving application data, replicate asynchronously to the passive standby cluster. In a disaster recovery scenario, you can cut over from the unavailable primary cluster to the standby cluster. This will stop the replication stream, reset the standby cluster to a point in time where all ingested data is consistent, and mark the standby as ready to accept application traffic. Physical cluster replication is in preview for CockroachDB Self-Hosted, and is an enterprise-only feature. To share feedback and/or issues, contact Support.
Super regions
Super regions allow you to define a set of database regions such that schema objects will have all of their replicas stored only in regions that are members of the super region. The primary use case for super regions is data domiciling.
cockroach
commands
The table below lists the cockroach
commands available in preview in CockroachDB.
Command | Description |
---|---|
cockroach demo |
Start a temporary, in-memory CockroachDB cluster, and open an interactive SQL shell to it. |
cockroach sqlfmt |
Reformat SQL queries for enhanced clarity. |