Introduction to MindsDB
Zoran Pandovski
MindsDB is an AI layer for existing databases that allows you to effortlessly and cost-effectively develop, train, and deploy state-of-the-art machine learning models using standard queries to get accurate business predictions using AI Tables.

Zoran Pandovski

August 24, 2020

Zoran is a full stack developer based in Macedonia. He works as MindsDB's senior full stack developer and works on everything from building and managing the website to supporting the open source product to working with users on their support questions.

The Democratization of all aspects of AI, including Machine Learning, is quite a hot topic nowadays. You can hear that the top 500 fortune companies in the world have recognized the value of Machine Learning or are already using it. But not just the top ones; any company or industry that works with large amounts of data shall gain an advantage over competitors by getting insights from the data itself. 

Suppose we try to think about the use cases of Machine Learning in the enterprise world. The possibilities are limitless: Healthcare, Financial Services, Retail, and Customer services. That said, any company that has data can innovate its podcast and services or optimize operations and its business decisions by applying Machine Learning. 

But, what should be the first steps for doing that? How can businesses apply Machine Learning? 

The first thing that comes to mind is by hiring a Data Scientist. In simple words, the Data Scientist helps the company to get the actionable insight from the data they have. Let’s quickly go over all of the steps of the Data Science process.

The lifecycle of a data science process includes all of the steps above. It covers different technical areas such as computer science, mathematics, statistics. It requires a combination of various skills, starting from technical expertise with a programming language or database (Python, SQL, R), domain knowledge, and tackling challenging business problems to solution measurements and implementations. Maybe that’s why Data Scientists are so expensive to hire. 

As Harvard Business Review quotes, “They are difficult and expensive to hire and, given the very competitive market for their services, difficult to retain.”

It is super hard to find good data scientists who have experience and knowledge to cover all relevant domains. 

What if the business can use their employees’ domain expertise with a lot of experience in the industry and just use a tool or find a way to cover the General Data Science Expertise? That would be a win-win situation for most of the business. So, is that even possible? The shortest answer is yes. Let’s say a welcome to MindsDB

In the following few sections, we will go over the MindsDB’s features that cover the steps that even non-technical people can do to apply Machine Learning.

MindsDB is an AI layer for existing databases that allows you to effortlessly and cost-effectively develop, train, and deploy state-of-the-art machine learning models using standard queries to get accurate business predictions using AI Tables.

MindsDB translates ideas into machine learning code to provide business insights. Regardless of the tech skills, data teams can develop in-house cost-effective machine learning models to get the insights needed to validate business theories using the available data, right where the data lives.

AI Tables

We start this introduction with an explanation about how businesses can get insights from the data. Data itself is the core of any Machine Learning algorithm. If we ask ourselves where all that data lives, the answer will always be the Databases. 

One of the great features of MindsDB is that it integrates with most of the top used database systems such as MySQL, MariaDB, PostgreSQL, MongoDB, MsSQL, ClickHouse. That said, any business can implement Machine Learning by simply connecting MindsDB directly to its database.

The simplicity of AI Tables is that they can be queried like regular databases. The complicated steps for feature engineering, data encoding/decoding, training models, etc. can now be done with a simple SQL query. When we say simple query, we mean

 SELECT <predicted_variable> FROM <ML_model> WHERE <conditions> 

That’s all. No complicated skills are required.


Simplicity makes things easy, right? The key goal of MindsDB is its simplicity. By using MindsDB, any employee can apply the Data Science process and get insights from the data. When we mention simplicity, we talk about:

  • Simple as one line of code or
  • Simple as one SQL query or
  • Simple as one click with the Scout (our Graphical User Interface)


Automated Machine Learning puts the power of Advanced Machine Learning closer to business users by automating most of the data science steps. MindsDB, as an AutoML system, covers the complete pipeline from the raw data to the deployable Machine Learning model. MindsDB is making the power of Machine Learning easier and accessible to everybody.


We already mentioned that MindsDB, as an Auto ML system, makes advanced ML easier. But, we also know that it is helpful to understand why and how it reaches its conclusions. MindsDB covers that too. As an Explainable AutoML system, its results can be understood by everyone. A few of the questions that MindsDB can answer after providing its predictions are:

  • What is relevant for this prediction?
  • When can you trust this prediction?
  • How accurate is this prediction?

Data Privacy (Trustworthy)

Consumers don’t want to do any business with companies that they can’t trust. Data privacy is one of the most significant and most important issues nowadays. MindsDB can be used and deployed on any trusted cloud provider. But, if your data is sensitive, you can deploy MindsDB Server on-premises and have full control over your data.

Instead of sharing your data externally or uploading it to the cloud providers, you can use MindsDB as a self-service provider and make sure that your data is accessible to only those who need it.