Databricks Community

Summary In production machine learning systems (like real-time recommenders or fraud detection), models operate under a strict latency budget (typically milliseconds end-to-end). Within this window, the model must fetch features, run inference, and r...

Summary One API, every client: Instead of building separate endpoints for each app or partner, GraphQL lets every consumer ask for exactly the data it needs — but typically requires a lot of backend plumbing.No backend required: A built-in Postgres e...

Summary Why systems catering to tactical, operational decision-making need to be different from traditional OLTP and OLAPHow a Lakebase-centric architecture for ODS solves this needWhat business use-cases gain value from an ODS build on top of Lakeba...

Introduction In today’s AI-native world, applications no longer rely on exact keyword matches—they understand meaning. This shift is powered by embeddings: numerical representations of text that capture semantic similarity. For instance, a user searc...

In today's dynamic application development landscape, it is paramount to be able to leverage your own custom libraries within an App environment. These libraries often contain proprietary logic, critical algorithms, or specific data access patterns t...