About RamDr. Ram Sriharsha held engineering, product management, and VP roles at the likes of Yahoo, Databricks, and Splunk. At Yahoo, he was both a principal software engineer and then research scientist; at Databricks, he was the product and engineering lead for the unified analytics platform for genomics; and, in his three years at Splunk, he played multiple roles including Sr Principal Scientist, VP Engineering and Distinguished Engineer.Links Referenced:
Pinecone: https://www.pinecone.io/

XKCD comic: https://www.explainxkcd.com/wiki/index.php/1425:_Tasks

TranscriptAnnouncer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.Corey: This episode is sponsored in part by our friends at Chronosphere. Tired of observability costs going up every year without getting additional value? Or being locked into a vendor due to proprietary data collection, querying, and visualization? Modern-day, containerized environments require a new kind of observability technology that accounts for the massive increase in scale and attendant cost of data. With Chronosphere, choose where and how your data is routed and stored, query it easily, and get better context and control. 100% open-source compatibility means that no matter what your setup is, they can help. Learn how Chronosphere provides complete and real-time insight into ECS, EKS, and your microservices, wherever they may be at snark.cloud/chronosphere that’s snark.cloud/chronosphere.Corey: This episode is brought to you in part by our friends at Veeam. Do you care about backups? Of course you don’t. Nobody cares about backups. Stop lying to yourselves! You care about restores, usually right after you didn’t care enough about backups. If you’re tired of the vulnerabilities, costs, and slow recoveries when using snapshots to restore your data, assuming you even have them at all living in AWS-land, there is an alternative for you. Check out Veeam, that's V-E-E-A-M for secure, zero-fuss AWS backup that won’t leave you high and dry when it’s time to restore. Stop taking chances with your data. Talk to Veeam. My thanks to them for sponsoring this ridiculous podcast.Corey: Welcome to Screaming in the Cloud. I’m Corey Quinn. Today’s promoted guest episode is brought to us by our friends at Pinecone and they have given their VP of Engineering and R&D over to suffer my various sling and arrows, Ram Sriharsha. Ram, thank you for joining me.Ram: Corey, great to be here. Thanks for having me.Corey: So, I was immediately intrigued when I wound up seeing your website, pinecone.io because it says right at the top—at least as of this recording—in bold text, “The Vector Database.” And if there’s one thing that I love, it is using things that are not designed to be databases as databases, or inappropriately referring to things—be they JSON files or senior engineers—as databases as well. What is a vector database?Ram: That’s a great question. And we do use this term correctly, I think. You can think of customers of Pinecone as having all the data management problems that they have with traditional databases; the main difference is twofold. One is there is a new data type, which is vectors. Vectors, you can think of them as arrays of floats, floating point numbers, and there is a new pattern of use cases, which is search.And what you’re trying to do in vector search is you’re looking for the nearest, the closest vectors to a given query. So, these two things fundamentally put a lot of stress on traditional databases. So, it’s not like you can take a traditional database and make it into a vector database. That is why we coined this term vector database and we are building a new type of vector dat