TensorFlow models

Tensorflow is a framework for creating neural networks. It implements basic linear algebra and multi-variable calculus operations in a scalable fashion, and allows users to easily chain these operations into a computation graph.

Vertica supports importing, exporting, and making predictions with TensorFlow 1.x and 2.x models trained outside of Vertica.

In-database TensorFlow integration with Vertica offers several advantages:

• Your models live inside your database, so you never have to move your data to make predictions.

• The volume of data you can handle is limited only by the size of your Vertica database, which makes Vertica particularly well-suited for machine learning on Big Data.

• Vertica offers in-database model management, so you can store as many models as you want.

• Imported models are portable and can be exported for use elsewhere.

When you run a TensorFlow model to predict on data in the database, Vertica calls a TensorFlow process to run the model. This allows Vertica to support any model you can create and train using TensorFlow. Vertica just provides the inputs - your data in the Vertica database - and stores the outputs.