All posts tagged with pgvector


We’re thrilled to launch our new Heroku Postgres Essential database plans. These plans have pgvector support, no row count limits, and come with a 32 GB option. We deliver exceptional transactional query performance with Amazon Aurora as the backing infrastructure. One of our beta customers said:

“The difference was noticeable right from the start. Heroku Postgres running on Aurora delivered a boost in speed, allowing us to query and process our data faster.”

Our Heroku Postgres Essential plans are the quickest, easiest, and most economical way to integrate a SQL database with your Heroku application. You can use these fully managed databases for a wide range of applications, such as...

We’re pleased to introduce the pgvector extension on Heroku Postgres. In an era where large language models (LLMs) and AI applications are paramount, pgvector provides the essential capability for performing high-dimensional vector similarity searches. This allows Heroku Postgres to quickly find similar data points in complex data, which is great for applications like recommendation systems and prompt engineering for LLMs. As of today, pgvector is fully compatible with all Production-tier databases running Postgres 15 at no additional charge and you can get started with a simple CREATE EXTENSION vector; command in your client session. In this post, we look at how you can use pgvector and...

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