What is Tinybird?
Tinybird is a next-generation, AI-native real-time analytics platform built from the ground up for developers who need to turn massive, fast-moving data into production-grade APIs—in seconds, not weeks. At its core lies a fully managed, optimized ClickHouse® engine—engineered not just for speed, but for developer velocity and AI readiness. With sub-100ms query latency on billions of rows, Tinybird eliminates the infrastructure drag of traditional OLAP stacks. No provisioning, no tuning, no scaling headaches: just SQL that compiles into secure, versioned, auto-scaling REST endpoints. Whether you're powering live dashboards for SaaS customers, detecting anomalies in IoT sensor streams, or serving personalized recommendations with vector-enhanced queries, Tinybird delivers real-time analytics as code—designed for how modern engineering teams actually build.
How to Use Tinybird
Start building in under a minute: install the tb CLI with curl https://tinybird.co | sh, authenticate, and run tb init to scaffold your first analytics project. From there, define data sources (via HTTP, Kafka, S3, or direct ingestion), write declarative SQL pipelines using Tinybird’s enhanced dialect—including native vector functions, time-windowed aggregations, and JOINs across streaming and historical layers—and instantly publish them as authenticated APIs. All development happens locally via Tinybird Container—a lightweight, Docker-based environment that mirrors production behavior, enabling full testing before deployment.
Adopt a GitOps workflow: commit your .sql files, schemas, and API definitions alongside application code. Push to your repo, and Tinybird’s CI/CD automatically validates, deploys, and versions every change—with one-click rollbacks and audit logs for every endpoint. For accelerated iteration, integrate Tinybird Code—the AI co-pilot IDE extension—that suggests optimized query patterns, detects performance anti-patterns, recommends RBAC policies based on usage, and even generates pipeline documentation from your SQL comments.