Steven Pousty

Vector Databases - what, why, and how

Monday, 11:00 AM EST

In the last two years, AI machine learning has exploded in prominence. One of the key concepts used in the modeling and storage of AI is vectors. There is no doubt vector data management will be a key concern of most people concerned with the lifecycle of data management. Feeling like you should learn more and how you would use them in your data work? Then have I got a talk for you!

We will start by explaining the concept of (embedding) vectors and how they are used in the AI life cycle. From there we will go into putting them into a database.

Now that those vectors are in a database we can talk about the use cases where the technology makes sense. As opposed to an RDBMS, vector databases are more tightly focused and optimized for particular use cases.

To ground this discussion in something more concrete, we will show live demos of the technology throughout the talks. By the time you leave you will have a strong base to go home and explore more (and impress friends at dinner parties).

wait What? Postgresql can do that?

Tuesday, 3:15 PM EST

You know, and probably already love, PostgreSQL as your relational database. But this session will show you all the other features you never knew Postgresql brought to the table. We will show you how you can forget about using ElasticSearch, MongoDB, and Redis for a broad array of use cases. The end goal of the session is to show you how Postgresql should be 80 of the 80/20 rule when choosing a datastore. Unless you have a specialized use case, PostgreSQL is the answer.