///

Como o SQLModel é baseado no SQLAlchemy, você pode facilmente usar **qualquer banco de dados suportado** pelo SQLAlchemy (o que também os torna suportados pelo SQLModel), como:

* PostgreSQL
* MySQL
* SQLite
* Oracle
* Microsoft SQL Server, etc.

Neste exemplo, usaremos **SQLite**, porque ele usa um único arquivo e o Python tem suporte integrado. Assim, você pode copiar este exemplo e executá-lo como está.

notify_nats           publish bucket notifications to NATS endpoints
notify_nsq            publish bucket notifications to NSQ endpoints
notify_mysql          publish bucket notifications to MySQL databases
notify_postgres       publish bucket notifications to Postgres databases
notify_elasticsearch  publish bucket notifications to Elasticsearch endpoints
notify_redis          publish bucket notifications to Redis datastores

///

В основе SQLModel лежит SQLAlchemy, поэтому вы спокойно можете использовать любую базу данных, поддерживаемую SQLAlchemy (и, соответственно, поддерживаемую SQLModel), например:

* PostgreSQL
* MySQL
* SQLite
* Oracle
* Microsoft SQL Server, и т.д.

* <a href="https://hub.docker.com/_/postgres" class="external-link" target="_blank">PostgreSQL</a>
* <a href="https://hub.docker.com/_/mysql" class="external-link" target="_blank">MySQL</a>
* <a href="https://hub.docker.com/_/mongo" class="external-link" target="_blank">MongoDB</a>
* <a href="https://hub.docker.com/_/redis" class="external-link" target="_blank">Redis</a>, usw.

///

As SQLModel is based on SQLAlchemy, you can easily use **any database supported** by SQLAlchemy (which makes them also supported by SQLModel), like:

* PostgreSQL
* MySQL
* SQLite
* Oracle
* Microsoft SQL Server, etc.

In this example, we'll use **SQLite**, because it uses a single file and Python has integrated support. So, you can copy this example and run it as is.

///

Como SQLModel se basa en SQLAlchemy, puedes usar fácilmente **cualquier base de datos soportada** por SQLAlchemy (lo que las hace también soportadas por SQLModel), como:

* PostgreSQL
* MySQL
* SQLite
* Oracle
* Microsoft SQL Server, etc.

En este ejemplo, usaremos **SQLite**, porque utiliza un solo archivo y Python tiene soporte integrado. Así que puedes copiar este ejemplo y ejecutarlo tal cual.

* <a href="https://hub.docker.com/_/postgres" class="external-link" target="_blank">PostgreSQL</a>
* <a href="https://hub.docker.com/_/mysql" class="external-link" target="_blank">MySQL</a>
* <a href="https://hub.docker.com/_/mongo" class="external-link" target="_blank">MongoDB</a>
* <a href="https://hub.docker.com/_/redis" class="external-link" target="_blank">Redis</a>, etc.

			Description:     "publish bucket notifications to NSQ endpoints",
			MultipleTargets: true,
		},
		config.HelpKV{
			Key:             config.NotifyMySQLSubSys,
			Description:     "publish bucket notifications to MySQL databases",
			MultipleTargets: true,
		},
		config.HelpKV{
			Key:             config.NotifyPostgresSubSys,
			Description:     "publish bucket notifications to Postgres databases",
			MultipleTargets: true,

        }

        if ("fess-crawler".equals(name)//
                || "fess-crawler-db".equals(name)//
                || "fess-crawler-db-h2".equals(name)//
                || "fess-crawler-db-mysql".equals(name)//
                || "fess-crawler-es".equals(name)//
                || "fess-crawler-opensearch".equals(name)//
                || "fess-crawler-lasta".equals(name)//

Это самый популярный Python-фреймворк, и он пользуется доверием.
Он используется для создания проектов типа Instagram.

Django довольно тесно связан с реляционными базами данных (такими как MySQL или PostgreSQL), потому использовать NoSQL базы данных (например, Couchbase, MongoDB, Cassandra и т.п.) в качестве основного хранилища данных - непросто.