Secure your spot and register now.

About the webinar

Data is at the heart of any AI project. From numerical data to videos or images, practitioners across all industries are looking for ways to efficiently store data and use it when building their models. PostgreSQL, the proven and well-loved database, can be a strong choice to support your AI in several ways.

What can PostgreSQL do for my AI application?

PostgreSQL is capable of efficiently storing and retrieving large amounts of data, such as training data for your models. Its wide support of the SQL standard, including SQL/MED, makes inspecting and querying that data a breeze. Moreover, PostgreSQL comes with similarity search capabilities, providing convenient index structures (GIST, GIN…) and built-in extensions (fuzzystrmatch, pg_trgm…).

Yet, there is more to PostgreSQL’s ecosystem than the database server. There are more than 1000 extensions for PostgreSQL, many of which can be useful for AI developers and users, for example pgvector and PostgresML.

The Role of PostgreSQL in MLOps

MLOps projects such as Kubeflow rely on relational databases for storing different artefacts, and choosing which relational database to use for MLOps is a common dilemma. We approached a similar topic in our recent webinar “PostgreSQL vs MySQL”, where we explored how, despite looking similar on the surface, the two databases are actually very different. The significant structural differences between databases can have a tremendous influence on the performance of any ML project, so understanding the possible impact is critical for both the enterprises who use these platforms and the engineers who develop them.

So how do we use PostgreSQL for machine learning?

Join the live discussion on February 8, 2024 to learn more about using PostgreSQL for AI projects. Led by Mohamed Nsiri, SQL Product Manager, and Andreea Munteanu, AI Product Manager, the webinar will cover:

• An overview of the PostgreSQL ecosystem for AI projects
• Benefits of PostgreSQL for AI projects
• Use cases where PostgreSQL should be used for AI projects