Machine Learning Capabilities Come to the Majority of Open Source Databases with MindsDB AI-Tables – PR Web

MindsDB

BERKELEY, Calif. (PRWEB) October 20, 2020

MindsDB, the open source AI layer for existing databases, today announced official integrations with open source relational databases PostgreSQL and MySQL. These join a growing list of integrations with community-driven databases including MariaDB and Clickhouse to bring the machine learning capabilities of MindsDB to over 55% of open source databases.

MindsDB brings machine learning to those who work with data to allow users to create and deploy ML models using standard SQL queries and increase AI projects efficiency. Through the use of AI-Tables, database users can apply machine learning models straight from their database and automatically generate predictions as simple as querying a table.

PostgreSQL is a powerful, open source object-relational database system with over 30 years of active community development. The database has a strong reputation for reliability, feature robustness, and performance. MySQL, owned by Oracle, is one of the most popular open source databases, trusted by organizations such as Facebook, Google, and Adobe. Together, the two represent 45% of the active open source database market.

The announcement was made as part of MindsDBs presentation during Percona Live Online 2020, the largest annual open source database conference.

Bringing machine learning resources to the open source database community is a huge part of our mission to democratize machine learning, said MindsDB co-founder, Adam Carrigan. Staying connected to this community has helped us identify the main challenges of users that know their data best and give them machine learning tools to help them solve those problems.

Bringing Machine Learning to the Database

I am excited to see MindsDB providing the power of machine learning, without leaving the convenience of SQL. There has been significant demand in the community for machine learning tools that work with on-premises data, can be run by the average database user, and are delivered cost-effectively, said Peter Zaitsev, CEO of Percona. As the open source database community gathers every year to share their knowledge at Percona Live, it is extremely exciting to see companies launch new solutions, like MindsDB with AI-Tables, that can expand what open source databases deliver to users.

With the newly announced MindsDB integrations, MySQL and PostgreSQL users can use AI-Tables to learn and make predictions from their data with no machine learning experiences. Users can now run a simple SQL query to deploy automated machine learning models directly inside their database.

The key to the MindsDB tool is the use of virtual AI-Tables which allow any user to easily train and test machine learning models with basic SQL as if they were standard database tables.

Community-focused Innovation

As more open source database users get hold of machine learning tools, it will be very exciting to see what the community will produce and how well benefit from AI and ML going forward, said OpenOcean Founder and General Partner Patrik Backman. Now is a good time for every database developer to get their hands dirty and try out with their own data how the MindsDB integration practically works.

While MindsDB is now available in over half of open source databases, we will continue to work towards our goal of democratizing machine learning for every database user, said Carrigan.

About MindsDB

MindsDB helps organizations to turn data into business predictions by adding machine learning capabilities to their databases. MindsDB provides an AI layer for existing databases that allows organizations to effortlessly and cost-effectively develop, train, and deploy state-of-the-art ML models using standard SQL queries to get accurate business predictions. Follow the company on LinkedIn, Twitter and Facebook and visit the blog for additional resources.

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Machine Learning Capabilities Come to the Majority of Open Source Databases with MindsDB AI-Tables - PR Web

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