Best alternatives to Spice AI in 2026

Getting data ready for AI agents or analytics traditionally means ETL — extract, transform, load — a whole engineering discipline built around copying data from scattered sources into one central warehouse before you can query it usefully. Spice AI's pitch is to skip that step: it federates SQL queries directly across your existing operational data sources in real time, so you query live data where it already lives instead of maintaining a separate synced copy. Beyond straightforward SQL federation and acceleration, it supports hybrid search combining vector, full-text, and keyword search in a single query, and can embed LLM inference calls directly inside SQL — letting an AI agent get both structured data and a model's interpretation of it in one round trip. It includes secure AI sandboxing for safely letting agents run generated queries, real-time change data capture, and edge-to-cloud deployment options with distributed observability. It's open source (Apache 2.0, github.com/spiceai/spiceai) founded by Luke Kim, with usage-based cloud pricing and a custom Enterprise tier that includes SOC 2 Type II compliance and a 99.9% uptime SLA; it's already deployed by companies including Twilio, Barracuda, and NRC Health.