CockroachDB Feature Availability

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Some CockroachDB features are made available in phases prior to being launched in general availability (GA). This page defines the different levels of CockroachDB v23.1 feature availability and lists the features in each phase.

Feature availability phases

Features in limited access

Export logs to Azure Monitor

Exporting logs to Azure Monitor from your CockroachDB Advanced 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 Advanced 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 Advanced 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 Advanced cluster to your chosen cloud metrics sink. To express interest and try it out, contact Support.

Features in preview

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.

CockroachDB Standard

CockroachDB Standard is a new plan for CockroachDB Cloud clusters and is in Preview. Compute for CockroachDB Standard is pre-provisioned and storage is usage-based. You can easily switch a CockroachDB Basic cluster to CockroachDB Standard in place.

GCP Private Service Connect for CockroachDB Advanced

Connecting privately to a CockroachDB Advanced cluster using GCP Private Service Connect is in preview. Private Service Connect allows you to selectively connect your cluster deployed on GCP to a VPC within your Google Cloud project.

Azure Private Link for CockroachDB Advanced

Connecting privately to a CockroachDB Advanced cluster using Azure Private Link is in preview. Azure Private Link allows you to selectively connect your cluster deployed on Azure to a virtual network within your Azure tenant.

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 Advanced clusters

Exporting metrics from CockroachDB Advanced to Amazon 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 Advanced cluster to your chosen cloud metrics sink.

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.

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.

>  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)

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 basic changefeed, which streams row-level changes to the client indefinitely until the underlying connection is closed or the changefeed is canceled. A basic 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:

• The server.child_metrics.enabled cluster setting must be set to true before using the metrics_label option. server.child_metrics.enabled is enabled by default in Standard and Basic.
• Metrics label information is sent to the _status/vars endpoint, but will not show up in debug.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.

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.

See Also

• SHOW {session variable}
• Functions and Operators
• ALTER TABLE ... EXPERIMENTAL_AUDIT
• SHOW TRACE FOR SESSION
• SHOW RANGE ... FOR ROW

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