All you need to know about Google Vertex AI Vector Search

The good and the bad stuff, no seriously, just a deep dive into the product

Vertex AI Vector Search previously known as Matching Engine.

Putting a similarity index into production at scale is a pretty hard challenge. It requires a whole bunch of infrastructure working closely together. You need to handle a large amount of data at low latency. It introduces you to topics like sharding, hashing, trees, load balancing, efficient data transfer, data replication, and much more.

That is nothing you want your team to work on. Rather use a well-implemented service like Google's Vertex AI Vector Search.

Vertex AI Vector Search provides the industry’s leading high scale, low latency, vector-similarity matching

Jump Directly to the Notebook and Code

All the code for this article is ready to use in a Google Colab notebook. If you have questions, please reach out to me via LinkedIn or Twitter.

Google Colaboratory

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