CloudBeaver – Web Database Manager

• Getting started
  • Application overview
  • License Management
  • Demo Server
  • FAQ
• Administration
  • Server configuration
  • Create Connection
  • Connection Templates Management
  • Access Management
    • Users
    • Teams
    • Users Provisioning
  • Authentication methods
    • Local Access Authentication
    • Anonymous Access Configuration
    • Reverse proxy header authentication
    • LDAP
    • Single Sign On
    • SAML
    • OpenID
    • AWS OpenID
    • AWS SAML
    • AWS IAM
    • AWS OpenId via Okta
    • Snowflake SSO
    • Okta OpenId
    • Cognito OpenId
    • JWT authentication
    • Kerberos authentication
    • NTLM
    • Microsoft Entra ID authentication
    • Google authentication
  • Database authentication methods
    • Database Native
    • MongoDB
    • Microsoft Entra ID
    • Oracle wallet
    • PostgreSQL Pgpass
    • Salesforce
  • Network configuration settings
    • SSH configuration
    • SSL configuration
  • User credentials storage
  • Cloud databases configuration
    • Cloud Explorer
    • Cloud storage
    • AWS Settings
  • Query Manager
  • Drivers Management
• Accessibility
• Keyboard shortcuts

• Features

  • Create Connection
  • Database navigator
    • Toolbar
    • Settings menu
    • Folders
    • Simple and Advanced View
  • Metadata editor
  • Properties editor
  • Data editor
    • Data Filters
    • Data Ordering
    • Value Panel
    • Grouping Panel
    • Result details Panel
    • Managing Charts
    • JSON and Document View
    • Working with GIS data
  • Data export
  • Data import
  • Entity Diagrams
  • SQL Editor
    • SQL Formatting
    • Query Execution Plan
    • Visual Query Builder
    • AI Smart Assistance
    • Auto and Manual commit modes
  • Log Viewer
  • Query History
  • Resource Manager
  • Session Manager
  • DBeaver Proxy driver

• Supported databases

  • File drivers
    • Multi Source
    • CSV
    • JSON
    • Parquet
    • XLSX
    • XML

• Server configuration
  • Configuring server datasources
  • Initial data configuration
  • Password policy
  • Secret Providers
  • Query manager database configuration
  • Server database
• Domain manager
• Product configuration parameters
• Command line parameters
• Log customization
• Local Preferences

• API

  • Server API explorer
  • API token generation

• AWS edition
• Enterprise edition

• Deployment options
• Additional setup and management
  • Version update
  • Workspace backup
  • SSL certificate configuration
  • How to connect CloudBeaver to a database on a separate machine in Azure
  • Nginx configuration
  • Configuring HTTPS for Jetty server

The Value Panel provides additional space in the Data editor in which you can manipulate data. The panel is handy if you work with complex types (structures, arrays), long text data or BLOBs.

To open the panel, click the Value button on the right hand side of the Data tab. Alternatively, you can open the Value panel by clicking Show the in value panel in the cell context menu.

To close the panel, click the Value button again.

The Value Panel displays just one value that is currently selected or in focus and allows editing.

At the top of the Value Panel, you can find several tabs. The tabs depend on the current value type. For example, if your current value is a string, you will find 4 tabs (Plain text, HTML, XML, JSON), each representing a format the string can be shown in.

There are 3 available tabs for BLOB type of data:

• Text
• HEX
• Base64

Note: This feature is available in Enterprise, AWS, Team editions only.

The Visual Query Builder is a user-friendly visualization tool that can help you to create queries to the database and see results. You do not need to know SQL language to work in it. The Visual Query Builder may be useful for:

• building queries;
• complex queries analysis;
• easy query editing.

To open the Visual Query Builder, click the Query Builder tab in the SQL Editor right toolbar.

1. Select tables in the Navigator tree and drag-and-drop them into the Visual Query Builder area. The existing connections between the tables will automatically be displayed. The tables will also be added to the SQL expression which can be found in the field to the right of the diagram.

2. To create a new join between tables, connect their columns holding the left mouse button. The connection between the selected columns of the tables will appear in the diagram and the Inner Join will be added to the SQL script.

3. You can change a join type clicking the join label on the connection line.
4. To remove a join between tables, click on the line, then press the Delete button. The connection will be removed from the diagram and the join will disappear from the SQL script.
5. By default all tables’ columns are included in the query. If you only want to see certain columns in your query result, select the checkbox near the column name.

6. WHERE condition with the filter value is used for filtering. To add a filter, write it in the top filter field.

Filter example:

7. To apply a sorting condition to a column, press the sorting icon next to a column name on the diagram. The column will be sorted in ascending order and the conditional expression ORDER BY will be added to the SQL script. To sort the column in descending order, press the sorting icon again to select the down arrow. If you want to remove a condition, continue to click the sorting icon to deactivate it. Sorting can be applied to multiple columns in different tables. First, apply sorting on the first column you wish to sort, and then on the second, third and so on. You can sort numbers, texts, dates, time and other values.

Use the Execute SQL statement button on the left pane to execute a query and get the results in the same tab. If you want to see the result in a new tab, press the Execute SQL statement in a new tab button .

You can use the same shortcuts as in the SQL Editor to execute the Visual Query.

The Visual Query Builder uses the following visual tools to display queries on the diagram:

Symbol	Description
	Table Primary Key is bold and displayed at the top of the table.
	Table Alias is used to shorten your Join Statement.
	Colored table header marks the first table in your Join Statement.
	Colorless header marks a joined table in your Join Statement.
	Line goes from the joined table to the first table.

Available Join types are described in the table below. The Visual Query Builder can show results only for those types of Joins that are supported by your database.

Symbol	Description
	Inner Join
	Left Join
	Left Outer Join
	Right Join
	Right Outer Join
	Full Join
	Full Outer Join
	Cross Join

You can customize the diagram view using the bottom toolbar to make the work with the diagram easier.

• Layout updates the diagram view to display all of its objects in the most optimal way.

• Zoom in and Zoom out enlarges or shrinks the diagram view.

• Settings menu contains additional settings of the Visual Query Builder. Press the Settings button at the bottom toolbar to open it.

  • Layout on update enables Auto-layout feature. As soon as you add a new object to the diagram, the diagram view will automatically be updated to display all of its objects in the most optimal way.
  • Show join type on entities moves Join labels from lines into headers of joined tables.
  • Show Type adds information about column types into entities.
  • Show Icons adds icons of column types into entities.
  • Notation changes the representation of connection lines. Simple notation is set by default. You can change it to the IDEF1X language type.

If you write a JOIN statement by yourself and then want to convert it to the diagram view, just switch the SQL Editor with your statement to the Visual Query Builder.

Note: the Visual Query Builder can transform the syntax of your query, but it does not affect the query result in the Result set.

CloudBeaver supports the visualization and management of spatial data. Spatial data, which includes geographic locations and geometric shapes.

Spatial data, often represented as either geometric or geographical values, can be visualized on a map or graph. A geometric object is typically composed of a sequence of points that define its shape. For a more comprehensive understanding of spatial data, you can refer to this detailed explanation.

CloudBeaver’s support of spatial data covers the following databases:

• PostgreSQL (PostGIS)
• Greenplum
• CockroachDB
• MySQL
• MariaDB
• SQLite (GeoPackage)
• H2GIS
• SAP HANA
• DuckDB
• Redshift
• Exasol
• Altibase
• BigQuery
• Oracle
• SQL Server
• Snowflake

• AlloyDB

To access the spatial data viewer, select one or more rows containing GIS data from your table. After selecting the rows, open the Value Panel to display the selected spatial data on a map. For more information, see Value Panel.

• Zooming: Allows you to zoom in and out to tailor the map view, using either the mouse wheel or the on-screen icons.
• Map display options: You can choose between street or topography map view.
• Data interaction: When you click on a spatial object on the map, CloudBeaver displays associated information from every other column in the corresponding row.
• Coordinate Reference System (CRS) selection: A dropdown menu in the viewer allows you to select the appropriate CRS for your data. For more information about CRS, see Spatial reference system.

By default, CloudBeaver stores all its files (configurations, scripts, etc.) in the

1. Locate the name of the running container:

   1. Open a terminal on the host machine.
   2. Run the following command to list all running containers in the Compose project:

      
      docker-compose ps
      
      

2. Identify the service name and open a shell inside the container:

   
   docker-compose exec <service_name> /bin/bash
   
   

   Replace

   <service_name>

   with the actual name of the service from your

   docker-compose.yml

   file.

3. After entering the container, navigate to the workspace directory:

   
   cd workspace/
   
   

CloudBeaver supports storing its workspace in an AWS S3 bucket. To enable this, update your

For more details on AWS S3 configuration, including setting up buckets, permissions, and best practices, see the official Amazon S3 Documentation

Make sure your CloudBeaver service includes the following environment variables:

services:

  cloudbeaver:

    environment:

      - AWS_ACCESS_KEY_ID=${AWS_ACCESS_KEY_ID}

      - AWS_SECRET_ACCESS_KEY=${AWS_SECRET_ACCESS_KEY}

      - AWS_REGION=${AWS_REGION}

      - CLOUDBEAVER_WORKSPACE_LOCATION=${CLOUDBEAVER_WORKSPACE_LOCATION}

AWS_ACCESS_KEY_ID=your-access-key

AWS_SECRET_ACCESS_KEY=your-secret-key

AWS_REGION=your-region

CLOUDBEAVER_WORKSPACE_LOCATION=s3:///dbeaver-downloads/test_workspace

It is possible to configure CloudBeaver to save database credentials (user names and passwords) in CloudBeaver storage.
In this case, users won’t need to enter database credentials every time they connect to a database.

However, the most secure way is to disable this option. See options “Save credentials” and “Save user credentials” in administrator console, page “Server configuration”.

There are two types of database connections: global and user.
Global connections are managed by CloudBeaver administrators, user connections are managed by users themselves.

Global database configuration is stored in workspace sub-folder

User configuration are stored in workspace sub-folders

Potentially, if an intruder/malware software will get access to CloudBeaver server filesystem, then it may get access to all stored user credentials. To increase security it is recommended to configure the server to keep workspace on a shared encrypted network folder (e.g. S3, see S3 Server-side encryption.

• How to configure S3 encrypted file system on Ubuntu

This article gives you an overview of how to create user in CloudBeaver.

There are two types of users:

• Local users: Created by the Administrator.
• AWS and Federated users: These users are managed externally through AWS or federated identity providers and are authorized to access the system via Single Sign-On (SSO).

For more information on Identity providers, see Authentication methods.

To create a new local user, follow these steps:

1. As an administrator, go to Settings -> Administration -> Users and Teams -> Teams.
2. Click on the + Create button.

3. Fill in the necessary details in the provided fields.

   

   Field Name	Description	Additional Info
   Username	Enter the desired username for the account.
   User password	Set a password for the account.	The user can change their password after initial setup.
   Repeat password	Re-enter the password for verification.
   User Status	Toggle to enable or disable the user.	Default status is Enabled.
   User Team	(Optional) Assign the user to one or more teams.	A team defines the permissions a user has within the system. For more information on teams, see Teams.
   First Name	(Optional) Provide the user’s first name.
   Last Name	(Optional) Provide the user’s last name.
   AWS Role ARN	(Optional) Enter the AWS Role ARN.	For more information about AWS roles, see AWS Settings.
   Microsoft Entra ID User ID	(Optional) Enter the Microsoft Entra ID.	For more information, see Microsoft Entra ID authentication.

4. To complete the process, click on the Create button.

   Once created, the user can be authenticated using local authentication methods. The user’s permissions will be determined by their assigned profile.

To allow a local user to authenticate through AWS/Federated auth methods, the local user’s username must match the user’s email address, which will connect via SSO (Single Sign-On). This alignment is necessary for the federated authentication process to succeed.

Note: This step is crucial during user creation as the username cannot be changed later.

CloudBeaver AWS Edition is designed to support only AWS and Federated users, excluding local user access. Therefore, it is not possible to create local users within this environment. Users must be imported into the system.

For more information, refer to Administration Users Provisioning.

The process of editing a user is similar to creating one, except you need to access an existing user.

When editing an existing user, you also have additional options:

In the Auth Methods tab, administrators can see and remove the authentication methods associated with a user.

You can remove an existing authentication method:

1. Select the desired method from the dropdown menu.
2. Click the DELETE button.

Tip: If you need to restore local authentication for the user, navigate to the Info tab and assign a new password to the user. This action will re-enable local authentication.

If you need to permanently remove a user from the system, you can do so through the Delete user option. When you attempt to delete a user, a confirmation dialog will appear to ensure that this action is intentional.

1. To delete a user, select the Delete option.

2. Follow the prompts in the dialog to confirm the deletion.

   

   Tip: If you prefer to keep the user but prevent their access, consider using the Disable option in the dialog. Alternatively, you can disable a user by selecting the checkbox in the Info section of the user profile.

CloudBeaver supports a wide range of databases, including relational, NoSQL, and embedded, providing easy integration with different systems and business needs.

Note: Not all databases in the list are available for connection by default. If you don’t see the database you need, contact your server administrator. For instructions on adding new database drivers, refer to the instruction.

• Apache Kyuubi
• ClickHouse
• Db2 iSeries/AS 400 for IBM i
• Db2 LUW
• DuckDB
• Firebird
• H2 Embedded
• MariaDB
• MySQL
• Oracle
• PostgreSQL
• SQL Server
• SQLite
• Trino

CloudBeaver Enterprise and AWS Editions include all databases supported in the Community Edition and additional databases for broader compatibility:

• Altibase
• Apache Arrow
• Apache Calcite Avatica
• Apache Kylin
• Azure Databricks
• Azure SQL Server
• Babelfish via TDS (beta)
• CUBRID
• Cache
• ClickHouse (Legacy)
• Cloudberry
• CloudSQL – MySQL
• CloudSQL – PostgreSQL
• CloudSQL – SQL Server
• CockroachDB
• CrateDB
• CrateDB (Legacy)
• Dameng
• Db2 for z/OS
• Denodo 8
• Derby Embedded
• Derby Server
• Dremio
• EDB
• Exasol
• Fujitsu Enterprise Postgres
• GaussDB
• Google AlloyDB
• Google Cloud Spanner
• Greenplum
• H2 Embedded V.2
• H2 Server
• H2GIS Embedded
• H2GIS Server
• HANA
• HSQL Embedded
• HSQL Server
• Informix
• Ingres
• InterSystems IRIS
• JDBCX
• Jennifer
• MS Access (UCanAccess)
• Materialize
• MaxDB
• Mimer SQL
• MonetDB
• MySQL 5 (Legacy)
• NDB Cluster
• NetSuite
• Netezza
• NuoDB
• ODBC
• OceanBase
• Ocient
• OmniSci (formerly MapD)
• OpenEdge
• OpenSearch
• Pervasive SQL
• PrestoDB
• PrestoSQL
• Raima
• Redshift
• Redshift Serverless
• RisingWave
• SAP ASE jConnect
• SQL Server (Old driver, jTDS)
• SQLite Crypt
• SQream DB
• Salesforce
• Salesforce Data Cloud
• SingleStore
• Snowflake
• StarRocks
• Sybase jConnect
• Sybase jTDS
• Teradata
• TiDB
• Vertica
• Virtuoso
• Yellowbrick

• YugabyteDB

• Apache Drill
• Apache Hive
• Apache Ignite
• Apache Phoenix
• Apache Spark
• Athena
• Cassandra
• Cloudera Impala
• CosmosDB (Cassandra)
• CosmosDB (MongoDB)
• CouchDB
• Couchbase
• Couchbase 5+
• CSV
• CUBRID
• DBF
• DocumentDB
• DynamoDB
• Elasticsearch
• Firestore
• Gemfire XD
• Google BigQuery
• Google Cloud Bigtable
• InfluxDB
• InfluxDB 2
• InfluxDB 3
• Kafka (ksqlDB)
• Keyspaces
• Machbase
• MongoDB
• Neo4j
• Neptune
• Open Distro Elasticsearch
• OrientDB
• Parquet
• Raima
• Redis
• ScyllaDB
• SnappyData
• Solr
• TDengine
• TDengine Cloud
• TimescaleDB
• Timestream
• XLSX
• Yugabyte CQL