Comparing PostgreSQL vs. MongoDB: Which Is Better for AI Workloads?

12 P.M. ET

Online Transaction Processing (OLTP) systems traditionally focus on managing small, consistent data chunks, such as those found in banking, e-commerce, and other transactional environments. For decades, Relational Database Management Systems (RDBMS) like PostgreSQL have excelled in such scenarios.

However, the rise of AI and machine learning applications has introduced new types of workloads that differ significantly from traditional OLTP requirements. These workloads require high throughput and the ability to manage and process vast amounts of data efficiently. This shift poses challenges for traditional RDBMS systems, which were not designed to handle the size, complexity, and variety of data typical of AI-driven environments.

In our latest webinar, “Comparing PostgreSQL vs. MongoDB: Which Is Better for AI Workloads?,” we reveal results from our benchmark tests between these two different database systems. The webinar will be presented by MongoDB Field CTO, Rick Houlihan, who has decades of experience working with RDBMS, PostgreSQL, and document databases like MongoDB. Register now and find out why it’s essential to consider database platforms specifically designed to handle large, complex data structures to effectively support modern AI applications.