This solution has a CPF query service that makes available the personal data stored in MySQL.
Each call in this service sends an event to an event queue on RabbitMQ.
A worker processes these events and stores them in MongoDB and updates the last record in Elasticsearch.

• Very sensible database - MySQL
• Light sensible database - MongoDB
• Fast database - Elasticsearch

It stores accounts data.

It stores events related data.

It stores the latest event associated to an account.

• Create .env file

MYSQL_ROOT_PASSWORD=example
RABBITMQ_DEFAULT_PASS=example
COMPOSE_FILE=docker-compose.yml:whois-api/nested-docker-compose.yml

• Run docker-compose

$ docker-compose up

• Run database migration

$ virtualenv venv
...

$ source venv/bin/activate

(venv) $ pip install -r requirements.txt
...

(venv) $ yoyo apply -p
Password for mysql://root@localhost/secure-database:
... applied

• Call whois-api endpoints