LanceDB: A Complete Search and Analytical Store for Serving Production-scale AI Applications
Overview
| Experience | In Person |
|---|---|
| Type | Breakout |
| Track | Artificial Intelligence |
| Industry | Enterprise Technology, Health and Life Sciences, Financial Services |
| Technologies | Apache Spark, Mosaic AI, PyTorch |
| Skill Level | Intermediate |
| Duration | 40 min |
If you're building AI applications, chances are you're solving a retrieval problem somewhere along the way. This is why vector databases are popular today. But if we zoom out from just vector search, serving AI applications also requires handling KV workloads like a traditional feature store, as well as analytical workloads to explore and visualize data. This means that building an AI application often requires multiple data stores, which means multiple data copies, manual syncing, and extra infrastructure expenses.
LanceDB is the first and only system that supports all of these workloads in one system. Powered by Lance columnar format, LanceDB completely breaks open the impossible triangle of performance, scalability, and cost for AI serving. Serving AI applications is different from previous waves of technology, and a new paradigm demands new tools.