Initially, MindsDB comprises three system databases and one default project, as follows:

  • information_schema stores metadata of all the objects such as handlers, databases, AI engines, models, jobs, and more.
  • log stores log data of models and jobs.
  • files, which is initially empty, stores all files uploaded to MindsDB.
  • mindsdb is the default project for storing models, views, jobs, triggers, adn agents.

List all databases by running the following SQL commands:


Here is the output:

| Database             | TYPE    | ENGINE |
| information_schema   | system  | [NULL] |
| log                  | system  | [NULL] |
| mindsdb              | project | [NULL] |
| files                | data    | files  |

The information_schema Database

The information_schema database contains all the system tables that correspond to MindsDB objects as follows:

HANDLERSStores all (data and AI) handlers, which are data integrations and AI integrations supported by MindsDB.
DATABASESStores all data sources connected to MindsDB. Note that corresponding handlers are required, and you can connect only the data sources supported by MindsDB after installing the required handler dependencies.
ML_ENGINESStores all AI/ML engines configured at MindsDB. Note that corresponding handlers are required, and you can connect only the AI/ML engines supported by MindsDB after installing the required handler dependencies.
MODELSStores all models deployed within the MindsDB ecosystem. Note that you can create and deploy a model only after configuring the corresponding AI/ML engine.
VIEWSStores all views created in MindsDB.
JOBSStores all jobs that facilitate workflow automation.
TRIGGERSStores all triggers that facilitate workflow automation.
AGENTSStores all AI agents created in MindsDB.
SKILLSStores all skills that can be assigned to AI agents.
KNOWLEDGE_BASESStores all knowledge bases that can be assigned to AI agents as skills.
CHATBOTSStores all chatbots that comprise an AI agent and a chat interface.

Some of the objects, including DATABASES, ML_ENGINES, and MODELS, may contain sensitive information in the form of API keys or passwords. MindsDB hides this sensitive information by default.

If you want to expose this sensitive information in the output when querying these objects, set the show_secrets flag to true.


And to hide them back, set it to false.


Use the SHOW command to list all objects as follows:

SHOW object_name
[FROM project_name]
[LIKE 'object_name_part%']
[WHERE key = value];

For instance, list all OpenAI models from the mindsdb project that contain ai in its name.

FROM mindsdb
LIKE '%ai%'
WHERE engine = 'openai';

Another example of how to query for the available data and AI handlers:

WHERE type = 'data';

WHERE type = 'ml';

Before you can connect a data source using a data handler or create a model using an AI handler, make sure that the IMPORT_SUCCESS column reads true. If it reads false, then install the dependencies for this handler before using it.

The mindsdb Project

MindsDB enables you to group all objects within projects. Projects can store models, views, jobs, triggers, agents, skills, knowledge bases, and chatbots.

Projects store all objects except for handlers, connected data sources, and configured AI/ML engines.

Note that based on the available handlers, you can connect a data source to MindsDB or configure an AI/ML engine within MindsDB. Having done that, you can, for instance, create a view with data from the connected data source and store it inside the project, or create a model based on the configured AI/ML engine and store it inside the project.

MindsDB provides the default mindsdb project where all objects created without defining a project are stored.

Learn more about how to create and manage projects here.

The files Database

It is another default database that stores all the files uploaded to MindsDB.

Here is how you can upload files to MindsDB.