There are myriad use cases for MindsDB, such as predicting customer behavior, reducing churn, improving employee retention, detecting anomalies in industrial processes, credit-risk scoring, and predicting inventory demand — it’s all about using existing data to figure out what that data might look like at a later date. Torres said that MindsDB enables what is known as In-Database ML (I-DBML) to create, train, and use ML models in SQL, as if they were tables in a database. “It brings ML as close to the data as possible, integrates the ML models as virtual database tables, and can be queried with simple SQL statements.” MindsDB ships in three broad variations — a free, open source incarnation that can be deployed anywhere; an enterprise version that includes additional support and services; and a hosted cloud product that recently launched in beta, which charges on a per-usage basis.
https://venturebeat.com/2021/11/07/mindsdb-wants-to-give-enterprise-databases-a-brain/
