This document discusses using Apache Spark to enable low-latency web queries through a persistent Spark context. It introduces FiloDB, a distributed, versioned, columnar analytics database built on Spark that allows for fast, updatable queries through efficient in-memory columnar storage and filtering. The document demonstrates running over 700 SQL queries per second on a dataset of 15 million NYC taxi records loaded into FiloDB through caching of SQL parsing and use of Spark's collectAsync to enable asynchronous query execution.